CN119006391A - Fluorescent staining system and method for fabric printing and dyeing - Google Patents
Fluorescent staining system and method for fabric printing and dyeing Download PDFInfo
- Publication number
- CN119006391A CN119006391A CN202411050788.7A CN202411050788A CN119006391A CN 119006391 A CN119006391 A CN 119006391A CN 202411050788 A CN202411050788 A CN 202411050788A CN 119006391 A CN119006391 A CN 119006391A
- Authority
- CN
- China
- Prior art keywords
- area
- dyeing
- fluorescent
- image
- fabric
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 239000004744 fabric Substances 0.000 title claims abstract description 251
- 239000007850 fluorescent dye Substances 0.000 title claims abstract description 214
- 238000007639 printing Methods 0.000 title claims abstract description 173
- 238000004043 dyeing Methods 0.000 title claims abstract description 168
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000011109 contamination Methods 0.000 claims abstract description 88
- 238000012545 processing Methods 0.000 claims abstract description 33
- 230000009467 reduction Effects 0.000 claims abstract description 10
- 238000001514 detection method Methods 0.000 claims description 37
- 238000004364 calculation method Methods 0.000 claims description 26
- 230000003068 static effect Effects 0.000 claims description 24
- 238000001914 filtration Methods 0.000 claims description 17
- 230000003993 interaction Effects 0.000 claims description 17
- 230000000694 effects Effects 0.000 claims description 14
- 230000007246 mechanism Effects 0.000 claims description 13
- 238000004458 analytical method Methods 0.000 claims description 12
- 238000005516 engineering process Methods 0.000 claims description 12
- 238000004891 communication Methods 0.000 claims description 10
- 238000003708 edge detection Methods 0.000 claims description 6
- 239000003086 colorant Substances 0.000 claims description 4
- 230000000007 visual effect Effects 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000013500 data storage Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
- 238000010191 image analysis Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims 1
- 239000000126 substance Substances 0.000 abstract description 8
- 239000004753 textile Substances 0.000 abstract description 7
- 238000007447 staining method Methods 0.000 abstract description 5
- 238000007689 inspection Methods 0.000 abstract description 3
- 230000008569 process Effects 0.000 description 9
- 238000010186 staining Methods 0.000 description 9
- 238000012757 fluorescence staining Methods 0.000 description 7
- 230000009286 beneficial effect Effects 0.000 description 4
- 239000002131 composite material Substances 0.000 description 4
- 238000003384 imaging method Methods 0.000 description 4
- 230000033764 rhythmic process Effects 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 239000006081 fluorescent whitening agent Substances 0.000 description 3
- 235000005811 Viola adunca Nutrition 0.000 description 2
- 240000009038 Viola odorata Species 0.000 description 2
- 235000013487 Viola odorata Nutrition 0.000 description 2
- 235000002254 Viola papilionacea Nutrition 0.000 description 2
- 239000000654 additive Substances 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 210000002345 respiratory system Anatomy 0.000 description 2
- 230000000996 additive effect Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Geometry (AREA)
- Computer Graphics (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- Treatment Of Fiber Materials (AREA)
Abstract
本发明公开了一种用于面料印染的荧光沾污系统和方法，属于纺织印染技术领域。本发明解决了现有方法易导致检测人员吸入有害物质的问题，通过面阵相机获取当前面料印染荧光沾污影像图片，对图片进行区域划分及降噪处理；采用Sobe l算法提取出面料印染荧光沾污影像图片中荧光沾污区域边缘像素，并计算出面料印染荧光沾污影像图片的总体面积和荧光沾污区域的实际面积；判断荧光沾污区域占据面料印染荧光沾污影像图片的总体面积的比例及其所属等级，并在超出沾污警示阈值的情况下发出警示音提醒客户端及时解决问题，从而避免检测人员长期处于检测车间所具有的弊端，优化了现有荧光沾污方法的实用性与安全性。
The invention discloses a fluorescent staining system and method for fabric printing and dyeing, and belongs to the technical field of textile printing and dyeing. The invention solves the problem that the existing method easily causes the inspector to inhale harmful substances, obtains the current fabric printing and dyeing fluorescent staining image picture through an area array camera, and performs regional division and noise reduction processing on the picture; uses the Sobel algorithm to extract the edge pixels of the fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture, and calculates the overall area of the fabric printing and dyeing fluorescent staining image picture and the actual area of the fluorescent staining area; judges the proportion of the fluorescent staining area in the overall area of the fabric printing and dyeing fluorescent staining image picture and its grade, and sends a warning sound to remind the client to solve the problem in time when the contamination warning threshold is exceeded, thereby avoiding the disadvantages of the inspector being in the inspection workshop for a long time, and optimizing the practicality and safety of the existing fluorescent staining method.
Description
Technical Field
The invention relates to the technical field of textile printing and dyeing, in particular to a fluorescent staining system and method for fabric printing and dyeing.
Background
The textile process in the production chain is complicated, and the additive is complicated, especially the functional textile. With the improvement of life quality and the enhancement of health consciousness, the requirements of people on the quality of textiles are continuously improved, and the limitation and detection of the content of harmful substances in the textiles are particularly important. Fluorescent staining of fabric is a common problem in the process of textile printing and dyeing, and refers to the phenomenon that non-fluorescent fabric (mainly the white cloth and the light-colored cloth) is stained with fluorescent substances in the process of processing; this often occurs in the process of incomplete cleaning of the associated equipment and environment, or the raw materials are not correspondingly distinguished, resulting in contamination of fluorescent materials onto non-fluorescent materials; fluorescent whitening agents are important chemical additives, and can effectively improve the whiteness of the substrate of the product.
The existing ultraviolet lamp irradiation observation method is one of the most common methods, the principle is based on that fluorescent whitening agents can absorb ultraviolet light and emit visible blue-violet fluorescence, and detection personnel need to observe the fluorescence on the surface of a sample on site by naked eyes to distinguish, so that the method is simple and easy to implement, but the detection personnel need to stay in an inspection workshop for a long time, and the respiratory tract is easy to inhale certain harmful substances of cloth and printing chemical varieties, so that the physical quality of workers is influenced, and the practicability of the existing fluorescence staining method is reduced.
Therefore, the existing demand is not met, and a fluorescent staining system and a method for fabric printing and dyeing are provided.
Disclosure of Invention
The invention aims to provide a fluorescent staining system and a method for fabric printing and dyeing, which are used for obtaining current fabric printing and dyeing fluorescent staining image pictures through an area array camera, and carrying out region division and noise reduction treatment on the pictures; respectively extracting the total edge pixels of the fabric printing and dyeing fluorescent staining image picture and the edge pixels of the fluorescent staining area by adopting a Sobe l algorithm, and calculating the total area of the fabric printing and dyeing fluorescent staining image picture and the actual area of the fluorescent staining area; judging the proportion of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture and the grade of the fluorescent staining area, and sending out warning sound to remind the client to solve the problem in time under the condition that the staining warning threshold value is exceeded, so that the defect that a detector is in a detection workshop for a long time is avoided, the practicability and the safety of the existing fluorescent staining method are optimized, and the problem in the background technology is solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a fluorescent staining system for fabric printing, comprising:
An image acquisition unit for
Shooting image data of the fabric to be detected through an area array camera to obtain fabric printing and dyeing fluorescent contamination image pictures, and transmitting the fabric printing and dyeing fluorescent contamination image pictures to an image analysis unit for analysis processing based on a 5G communication technology in real time;
An image processing unit for
Filtering and noise reduction treatment is carried out on the fabric printing and dyeing fluorescent stain image picture, and the fabric printing and dyeing fluorescent stain image picture after the noise reduction treatment is obtained; the color tone adjustment is carried out on the current fabric printing and dyeing fluorescent stain image picture, and the fluorescent stain area in the fabric printing and dyeing fluorescent stain image picture is defined;
A contamination calculating unit for
Dividing and extracting the areas of the fluorescent stains in the fabric printing and dyeing fluorescent stains image pictures by an edge calculation method, and calculating the total area of the fabric printing and dyeing fluorescent stains image pictures and the area of the fluorescent stains area pictures;
A contamination analysis unit for
Analyzing the proportion of the area of the fluorescent staining area graph to the total area of the fabric printing and dyeing fluorescent staining image graph, and judging the severity of fluorescent staining of the fabric after printing and dyeing according to the current judgment;
Man-machine interaction platform for
Displaying an operation interface of the fluorescent staining system, and displaying the processing progress of the fabric printing and dyeing fluorescent staining image picture and the fluorescent staining processing result to a client in real time.
Further, the camera shooting array module comprises:
the static variable determining module is used for obtaining the size of the fabric, the thickness of the fabric and the position of the light source of the fabric to be detected, and establishing a static scene variable based on specific characteristics of the size of the fabric, the thickness of the fabric and the position of the light source;
the dynamic variable determining module is used for acquiring the activity characteristics of the fabric to be detected in the camera shooting range and establishing dynamic scene variables based on the activity characteristics;
The coordinate determining module is used for establishing a three-dimensional shooting scene based on the static scene variable and the dynamic scene variable, determining the coordinate position of the static scene variable in the three-dimensional shooting scene and determining the coordinate activity range of the dynamic scene variable in the three-dimensional shooting scene;
the integrated set determining module is used for designing an initial camera array integrated set of the area array camera based on the shooting range characteristics of the area array camera and the coordinate positions of the static scene variables in the three-dimensional shooting scene and combining the number of the area array cameras;
The weight determining module is used for setting variable weights of static scene variables in a three-dimensional shooting scene based on shooting difficulty and setting coordinate weights of coordinate positions of a fabric area based on fabric visual characteristics;
The integrated processing module is used for determining the shooting weighting precision of the fabric to be detected by combining the variable weight and the coordinate weight when shooting is carried out according to each initial camera array in the initial camera array integrated set, and selecting a target camera array integrated set with the shooting weighting precision greater than the preset precision from the initial camera array integrated set;
The array determining module is used for determining a dynamic area for fabric detection based on a coordinate moving range of a dynamic scene variable in a three-dimensional shooting scene, determining a detection frequency and a detection angle of each camera array in the target camera array set for the dynamic area, and selecting a camera array with the optimal detection frequency and detection angle as a target camera array;
And the shooting module is used for shooting the fabric to be detected by using the target camera array to obtain a fabric printing and dyeing fluorescent stain image picture.
Further, the image acquisition unit includes
The camera shooting and arranging module is used for ensuring that complete fabric printing and dyeing fluorescent stain image pictures are obtained in a short time through a camera array formed by a plurality of area array cameras transversely;
And the wireless transmission module is used for transmitting the fabric printing and dyeing fluorescent stain image picture to the image processing unit in real time through a 5G communication technology for carrying out picture pretreatment to obtain the fabric printing and dyeing fluorescent stain image picture with clear pixels.
Further, the image processing unit comprises
The region dividing module is used for marking out a fabric fluorescent contamination region and a fabric fluorescent non-contamination region by different colors in fabric printing and dyeing fluorescent contamination image pictures to be identified by adopting photoshop software, and distinguishing different image components in the fabric printing and dyeing fluorescent contamination image pictures;
And the filtering processing module is used for carrying out weighted average filtering processing on the fabric printing and dyeing fluorescent stain image pictures by adopting a Gaussian filtering method, so that the noise remained in the fabric printing and dyeing fluorescent stain image pictures is reduced.
Further, the contamination calculating unit includes
The edge calculation module is used for carrying out edge detection on a fluorescent contamination area in a fabric printing and dyeing fluorescent contamination image picture by adopting a Sobe l algorithm, finding out the number of all pixel points in the edge of the fluorescent contamination area, and calculating the actual area of the fluorescent contamination area;
The duty ratio calculation module is used for calculating the proportion of the actual area of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture, and obtaining the staining duty ratio of the fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture.
Further, the edge calculation module includes:
The pixel point analysis module is used for acquiring a suspicious edge area of the fluorescent staining area, printing and dyeing an image gray value and an image gradient value of each pixel point in the suspicious edge area in the fluorescent staining image picture on the fabric by adopting a Sobe l algorithm, and the calculation formula is as follows:
Wherein G represents the image gray level of the pixel point, θ represents the image gradient value of the pixel point, gx represents the image gray level detected by the pixel point transversely, and Gy represents the image gray level detected by the pixel point longitudinally;
The pixel point evaluation module is used for calculating the comprehensive score of each pixel point according to the following formula based on the image gray value and the image gradient value of each pixel point;
Wherein K represents the composite score of the pixel points, sigma 1 represents the duty ratio of the image gray value in the edge point determination, and sigma 2 represents the duty ratio of the image gradient value in the edge point determination;
and the area calculation module is used for selecting the pixel points with the comprehensive score larger than the preset score as target pixel points and calculating the actual area of the fluorescence contamination area based on the number of the target pixel points.
Furthermore, before calculating the actual area of the fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture, the edge calculating module needs to determine the length and the width of the fabric printing and dyeing fluorescent staining image picture, and calculates the total area value of the fabric printing and dyeing fluorescent staining image picture.
Further, the contamination analysis unit includes
The grade establishing module is used for establishing a corresponding pollution proportion grade mechanism according to the proportion of the actual area of the fluorescence pollution area to the total area of the fabric printing and dyeing fluorescence pollution image picture;
The grade assessment module is used for judging the grade of the area occupation ratio of the fluorescent staining areas in the current fabric printing and dyeing fluorescent staining image picture according to the pollution occupation ratio grade mechanism, and judging the severity of the fluorescent staining in the current fabric printing and dyeing fluorescent staining image picture based on the grade of the occupation ratio;
And the result output module is used for displaying the severity of the fluorescent staining in the current fabric printing and dyeing fluorescent staining image picture on the man-machine interaction platform through a 5G communication technology and assisting a client to check.
Further, the man-machine interaction platform comprises
The staining warning module is used for setting a fluorescence staining warning threshold, and sending out warning sound through the buzzer when the severity of fluorescence staining in the current fabric printing and dyeing fluorescence staining image picture exceeds the warning threshold, so as to remind a client of timely solving the problem;
And the data storage module is used for storing the processed fabric printing and dyeing fluorescent stain image pictures and the fluorescent stain calculation results according to time sequences.
A method of fluorescent staining for fabric printing, comprising the steps of:
s1, obtaining a current fabric printing and dyeing fluorescent stain image picture by arranging an area array camera array;
s2, carrying out region division on the current fabric printing and dyeing fluorescent staining image picture, and extracting fabric fluorescent staining regions and fabric fluorescent non-staining regions through different tones;
S3, filtering the fabric printing and dyeing fluorescent stain image pictures after the region division, and eliminating noise in the pictures;
S4, calculating the total area of the fabric printing and dyeing fluorescent staining image picture by adopting a Sobe l algorithm, and then calculating the actual area of a fluorescent staining area in the picture according to the same steps;
S5, calculating the proportion of the actual area of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture;
s6, presetting a duty ratio grade mechanism and a contamination warning threshold value, firstly judging the grade of the current fluorescence contamination area duty ratio, and transmitting the signal to a man-machine interaction platform for display; the man-machine interaction platform compares the current fluorescence contamination duty ratio grade contamination warning threshold value, and sends out warning sound under the condition that the current fluorescence contamination duty ratio grade contamination warning threshold value exceeds the contamination warning threshold value, so that a client is reminded to solve the problem in time.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, the current fabric printing and dyeing fluorescent contamination image picture is obtained through the area array camera, and then the picture is subjected to area division and noise reduction treatment to obtain a clearer fabric printing and dyeing fluorescent contamination image picture; extracting edge pixels of a fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture by adopting a Sobe l algorithm, and calculating the total area of the fabric printing and dyeing fluorescent staining image picture and the actual area of the fluorescent staining area; judging the proportion of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture and the grade of the fluorescent staining area, and sending out warning sound under the condition that the staining warning threshold value is exceeded, thereby reminding a client to solve the fluorescent staining problem in the fabric in time, avoiding the defects of detection personnel in a detection workshop for a long time, and optimizing the practicability and safety of the existing fluorescent staining method.
Drawings
FIG. 1 is a schematic diagram of a system for fabric dyeing in accordance with the present invention;
FIG. 2 is a flow chart of a method of the present invention for fluorescent staining for fabric printing.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problem that the existing ultraviolet lamp irradiation observation method is one of the most common methods for judging fluorescent staining in fabric printing and dyeing, the principle is based on the fact that fluorescent whitening agents can absorb ultraviolet light and emit visible blue-violet fluorescence, detection personnel need to observe the fluorescence on the surface of a sample on site by naked eyes to distinguish, the method is simple and easy to implement, but the detection personnel need to stay in an inspection workshop for a long time, the respiratory tract is easy to inhale certain harmful substances of cloth and printing chemical varieties, and the physical quality of workers is influenced, so that the technical problem of the practicability of the existing fluorescent staining method is reduced, and referring to fig. 1-2, the embodiment provides the following technical scheme:
a fluorescent staining system for fabric printing, comprising:
An image acquisition unit for
Shooting image data of the fabric to be detected through an area array camera to obtain fabric printing and dyeing fluorescent contamination image pictures, and transmitting the fabric printing and dyeing fluorescent contamination image pictures to an image analysis unit for analysis processing based on a 5G communication technology in real time; specifically, the area array camera mainly adopts continuous and planar scanning light to realize detection of the fabric, can acquire complete fabric images at one time, and can acquire images in time; the camera has the advantages of simple structure, easy use and maintenance, and the pixel quantity and the pixel size can be adjusted according to the needs so as to adapt to different shooting requirements.
An image acquisition unit comprising:
the camera shooting and arranging module is used for ensuring that complete fabric printing and dyeing fluorescent stain image pictures are obtained in a short time through a camera array formed by a plurality of area array cameras transversely;
in this embodiment, for example: a certain room is selected in certain printing and dyeing to be used as a fabric printing and dyeing post-fluorescent staining detection room, and a plurality of camera placement points are transversely distributed in the room to form a camera array for shooting fabric printing and dyeing fluorescent staining image pictures.
And the wireless transmission module is used for transmitting the fabric printing and dyeing fluorescent stain image picture to the image processing unit in real time through a 5G communication technology for carrying out picture pretreatment to obtain the fabric printing and dyeing fluorescent stain image picture with clear pixels.
An image processing unit for
Filtering and noise reduction treatment is carried out on the fabric printing and dyeing fluorescent stain image picture, and the fabric printing and dyeing fluorescent stain image picture after the noise reduction treatment is obtained; the color tone adjustment is carried out on the current fabric printing and dyeing fluorescent stain image picture, and the fluorescent stain area in the fabric printing and dyeing fluorescent stain image picture is defined; an image processing unit comprising:
The region dividing module is used for marking out a fabric fluorescent contamination region and a fabric fluorescent non-contamination region by different colors in fabric printing and dyeing fluorescent contamination image pictures to be identified by adopting photoshop software, and distinguishing different image components in the fabric printing and dyeing fluorescent contamination image pictures; specifically, photoshop CS6 software is loaded in a man-machine interaction platform, a fabric printing and dyeing fluorescent stained image picture is opened in the software, a part of a fabric fluorescent non-stained area is selected through color, and a selection-color range is clicked; then the color range setting window is opened, and a suction pipe tool is used by default; clicking the fluorescent stained area of the fabric, and displaying the non-stained area of the fabric to be selected, wherein the non-stained area of the fabric is white; clicking the sampling tool, clicking the fluorescence contamination area of the fabric, and adding the fluorescence contamination area into the selection area; clicking to confirm, then from the ant line, both areas become selection areas; according to the operation, the areas, which are not stained by the fluorescence of the fabric, in the fabric printing and dyeing fluorescence stained image picture can be marked with the same color, so that the areas, which are stained by the fluorescence of the fabric, and the areas, which are not stained by the fluorescence of the fabric, are formed into different background colors, and the area attributes of the areas are conveniently distinguished.
The filtering processing module is used for carrying out weighted average filtering processing on the fabric printing and dyeing fluorescent stain image pictures by adopting a Gaussian filtering method, so that the noise remained in the fabric printing and dyeing fluorescent stain image pictures is reduced; specifically, gaussian filtering is a linear smoothing filtering technology, which is implemented by a process of weighted average on the whole image, wherein the value of each pixel point is obtained by weighted average of the value of each pixel point and other pixel values in the neighborhood; the processing mode can effectively smooth images and reduce noise, and particularly has obvious effect in processing Gaussian noise; and the calculation process is relatively simple and quick, so that the Gaussian filter method is very suitable for real-time image processing after fabric printing and dyeing.
In one embodiment, the camera shooting array module comprises:
the static variable determining module is used for obtaining the size of the fabric, the thickness of the fabric and the position of the light source of the fabric to be detected, and establishing a static scene variable based on specific characteristics of the size of the fabric, the thickness of the fabric and the position of the light source;
the dynamic variable determining module is used for acquiring the activity characteristics of the fabric to be detected in the camera shooting range and establishing dynamic scene variables based on the activity characteristics;
The coordinate determining module is used for establishing a three-dimensional shooting scene based on the static scene variable and the dynamic scene variable, determining the coordinate position of the static scene variable in the three-dimensional shooting scene and determining the coordinate activity range of the dynamic scene variable in the three-dimensional shooting scene;
the integrated set determining module is used for designing an initial camera array integrated set of the area array camera based on the shooting range characteristics of the area array camera and the coordinate positions of the static scene variables in the three-dimensional shooting scene and combining the number of the area array cameras;
The weight determining module is used for setting variable weights of static scene variables in a three-dimensional shooting scene based on shooting difficulty and setting coordinate weights of coordinate positions of a fabric area based on fabric visual characteristics;
The integrated processing module is used for determining the shooting weighting precision of the fabric to be detected by combining the variable weight and the coordinate weight when shooting is carried out according to each initial camera array in the initial camera array integrated set, and selecting a target camera array integrated set with the shooting weighting precision greater than the preset precision from the initial camera array integrated set;
The array determining module is used for determining a dynamic area for fabric detection based on a coordinate moving range of a dynamic scene variable in a three-dimensional shooting scene, determining a detection frequency and a detection angle of each camera array in the target camera array set for the dynamic area, and selecting a camera array with the optimal detection frequency and detection angle as a target camera array;
And the shooting module is used for shooting the fabric to be detected by using the target camera array to obtain a fabric printing and dyeing fluorescent stain image picture.
In this embodiment, the active features within the imaging range of the fabric to be detected include flipping movement of the fabric, and the like.
In this embodiment, it is determined that the imaging weighting accuracy of the fabric to be detected is that the greater the number of imaging captures for the position with the greater the coordinate weight is, the greater the imaging influence of the variable weight on the fabric area to be detected is, and the greater the corresponding weighting accuracy is.
In this embodiment, the lower the static scene variable is for the photography difficulty, the higher the corresponding variable weight.
The beneficial effects of above-mentioned design scheme are: acquiring the size of the fabric to be detected, the thickness of the fabric and the position of the light source, and establishing a static scene variable based on the specific characteristics of the size of the fabric, the thickness of the fabric and the position of the light source; acquiring activity characteristics in a shooting range of the fabric to be detected, and establishing dynamic scene variables based on the activity characteristics; establishing a three-dimensional shooting scene based on the static scene variable and the dynamic scene variable, determining the coordinate position of the static scene variable in the three-dimensional shooting scene, and determining the coordinate activity range of the dynamic scene variable in the three-dimensional shooting scene; based on the shooting range characteristics of the area array cameras and the coordinate positions of static scene variables in the three-dimensional shooting scene, combining the number of the area array cameras, and designing an initial camera array set of the area array cameras; setting variable weights of static scene variables in a three-dimensional shooting scene based on shooting difficulty, and setting coordinate weights of coordinate positions of a fabric area based on fabric visual characteristics; determining the shooting weighting precision of the fabric to be detected by combining variable weights and coordinate weights when shooting is carried out according to each initial camera array in the initial camera array collection, and selecting a target camera array collection with the shooting weighting precision greater than the preset precision from the initial camera array collection; determining a dynamic region detected by the fabric based on a coordinate moving range of a dynamic scene variable in a three-dimensional shooting scene, determining a detection frequency and a detection angle of each camera array in a target camera array combination for the dynamic region, and selecting a camera array with the comprehensive optimal detection frequency and detection angle as a target camera array; shooting the fabric to be detected by using the target camera array to obtain fabric printing and dyeing fluorescent contamination image pictures, realizing the accurate arrangement of the camera array, ensuring the accuracy of the obtained fabric printing and dyeing fluorescent contamination image pictures, and providing a basis for the follow-up fluorescent contamination detection.
A contamination calculation unit for
Dividing and extracting the areas of the fluorescent stains in the fabric printing and dyeing fluorescent stains image pictures by an edge calculation method, and calculating the total area of the fabric printing and dyeing fluorescent stains image pictures and the area of the fluorescent stains area pictures; a contamination calculating unit comprising:
The edge calculation module is used for carrying out edge detection on a fluorescent contamination area in a fabric printing and dyeing fluorescent contamination image picture by adopting a Sobe l algorithm, finding out the number of all pixel points in the edge of the fluorescent contamination area, and calculating the actual area of the fluorescent contamination area; secondly, before calculating the actual area of the fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture, the edge calculating module needs to determine the length and the width of the fabric printing and dyeing fluorescent staining image picture, and calculates the total area value of the fabric printing and dyeing fluorescent staining image picture;
In one embodiment, the edge calculation module includes:
The pixel point analysis module is used for acquiring a suspicious edge area of the fluorescent staining area, printing and dyeing an image gray value and an image gradient value of each pixel point in the suspicious edge area in the fluorescent staining image picture on the fabric by adopting a Sobe l algorithm, and the calculation formula is as follows:
Wherein G represents the image gray level of the pixel point, θ represents the image gradient value of the pixel point, gx represents the image gray level detected by the pixel point transversely, and Gy represents the image gray level detected by the pixel point longitudinally;
The pixel point evaluation module is used for calculating the comprehensive score of each pixel point according to the following formula based on the image gray value and the image gradient value of each pixel point;
Wherein K represents the composite score of the pixel points, sigma 1 represents the duty ratio of the image gray value in the edge point determination, and sigma 2 represents the duty ratio of the image gradient value in the edge point determination;
and the area calculation module is used for selecting the pixel points with the comprehensive score larger than the preset score as target pixel points and calculating the actual area of the fluorescence contamination area based on the number of the target pixel points.
In this embodiment, the sum of the duty ratio of the image gradation value in the edge point determination and the duty ratio of the image gradient value in the edge point determination is 1, and σ 1>σ2.
In this embodiment, the suspicious edge region is a region that can be used as an edge from which further determination is needed.
In this embodiment, the composite score of the pixel points is used to represent the probability that the pixel points can be edge points, and the higher the composite score, the higher the probability.
In this embodiment, the preset score is set according to the actual situation.
The beneficial effects of above-mentioned design scheme are: the method comprises the steps of obtaining a suspicious edge area of a fluorescence contamination area, printing and dyeing an image gray value and an image gradient value of each pixel point in the suspicious edge area in a fluorescence contamination image picture on a fabric by adopting a Sobe l algorithm, calculating a comprehensive score of each pixel point based on the image gray value and the image gradient value of each pixel point, selecting the pixel points with the comprehensive score being larger than a preset score as target pixel points, calculating the actual area of the fluorescence contamination area based on the number of the target pixel points, considering the gray value and the gradient value of the pixel points, adding the duty ratio condition, ensuring the accuracy of the obtained target pixel points as the edge points, and finally ensuring the accuracy of calculating the actual area of the fluorescence contamination area.
In the above embodiment, the edge detection is performed by using a Sobe l algorithm, which specifically includes: firstly defining a Sobe l operator template: the Sobe l operator has two 3x3 convolution kernels, one for detecting an edge Gx in the horizontal direction and the other for detecting an edge Gy in the vertical direction; these convolution kernels are generally defined as: horizontal direction Gx: [ -1,0,1; -2,0,2; -1,0,1], vertical Gy: [ -1, -2, -1;0, 0;1,2,1]; and (3) performing convolution operation: carrying out convolution operation on the Sobe l operator template and each pixel of the image, carrying out multiplication operation on each pixel and surrounding pixels, and then adding products to obtain a result; this process is performed in the horizontal and vertical directions, respectively, to calculate the gradient of the image in both directions; and then calculating the gradient amplitude and direction: after the gradient calculation in the horizontal and vertical directions is completed, the gradient amplitude G and the gradient direction theta of each pixel in the image can be calculated through a formula, the gradient amplitude G is obtained by calculating the square root of the sum of Gx 2 and Gy 2, and the gradient direction theta is obtained by calculating the ratio of Gy to Gx through an atan2 function; and finally, edge detection: edge detection can be performed according to gradient amplitude, and pixel points with larger gradient amplitude are likely to be edge points in an image, so that edge information on each pixel is determined, namely: obtaining the number of all pixel points in the edge; secondly, after the number of all pixel points in the edge is obtained, the actual area of the fluorescence contamination area is calculated according to the following steps: first determining the resolution of the image: typically expressed in dots per inch, the resolution of the image is critical to converting the number of pixels to the actual area, as it determines the actual size represented by each pixel in the image; and secondly, calculating the actual size represented by each pixel: calculating the length and width of each pixel represented in actual physical dimensions in inches by obtaining the DPI of the image; and finally, calculating the total area: the calculated actual size (length and width) represented by each pixel is multiplied by the total number of pixels to obtain the area of the entire image area.
The duty ratio calculation module is used for calculating the proportion of the actual area of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture, and obtaining the staining duty ratio of the fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture;
The above embodiments are followed, for example: the length of the fabric printing and dyeing fluorescent stain image picture is 54mm, the width is 39mm, and the area calculation formula is adopted: obtaining the total area of 2120mm 2 of the fabric printing and dyeing fluorescent stain image picture; if the actual area of the fluorescence contamination area is obtained according to the steps: 150mm 2; and then according to the duty ratio formula: number ∈ total x 100 = percentage: 150 ≡2120×100= 2.3584, taking two decimal places, it shows that the actual area of the fluorescent staining area is 2.35% of the total area of the fabric printed fluorescent staining image picture, and so on, so as to obtain the proportion of the fluorescent staining area in each fabric picture to the total area of the fabric printed fluorescent staining image picture.
A contamination analysis unit for
Analyzing the proportion of the area of the fluorescent staining area graph to the total area of the fabric printing and dyeing fluorescent staining image graph, and judging the severity of fluorescent staining of the fabric after printing and dyeing according to the current judgment; a contamination analysis unit comprising:
the grade establishing module is used for establishing a corresponding pollution proportion grade mechanism according to the proportion of the actual area of the fluorescence pollution area to the total area of the fabric printing and dyeing fluorescence pollution image picture;
The above embodiments are followed, for example: according to the actual duty ratio of the fluorescent staining area, the actual area of the fluorescent staining area accounting for 1% -10% of the total area of the fabric printing and dyeing fluorescent staining image picture can be regarded as the primary, the actual area of the fluorescent staining area accounting for 10% -20% of the total area of the fabric printing and dyeing fluorescent staining image picture is regarded as the intermediate level, and the actual area of the fluorescent staining area accounting for more than 20% of the total area of the fabric printing and dyeing fluorescent staining image picture is regarded as the high level, so that a pollution duty ratio level mechanism is established.
The grade assessment module is used for judging the grade of the area occupation ratio of the fluorescent staining areas in the current fabric printing and dyeing fluorescent staining image picture according to the pollution occupation ratio grade mechanism, and judging the severity of the fluorescent staining in the current fabric printing and dyeing fluorescent staining image picture based on the grade of the occupation ratio;
The above embodiments are followed, for example: through the calculation, the actual area of the fluorescent staining area accounts for 2.35% of the total area of the fabric printing and dyeing fluorescent staining image picture, the current duty ratio is 2.35% according with the primary mechanism in the pollution duty ratio grade mechanism by referring to the established pollution duty ratio grade mechanism, the severity of the fluorescent staining in the fabric printing and dyeing fluorescent staining image picture is obtained to be at the primary level, and the current result is transmitted and displayed in the man-machine interaction platform through the 5G communication technology.
And the result output module is used for displaying the severity of the fluorescent staining in the current fabric printing and dyeing fluorescent staining image picture on the man-machine interaction platform through a 5G communication technology and assisting a client to check.
Man-machine interaction platform for
Displaying an operation interface of the fluorescent staining system, and displaying the processing progress of the fabric printing and dyeing fluorescent staining image picture and the fluorescent staining processing result to a client in real time; a human-machine interaction platform, comprising:
The staining warning module is used for setting a fluorescence staining warning threshold, and sending out warning sound through the buzzer when the severity of fluorescence staining in the current fabric printing and dyeing fluorescence staining image picture exceeds the warning threshold, so as to remind a client of timely solving the problem;
The above embodiments are followed, for example: regarding the fluorescence contamination area with the proportion of 1-10% as a primary, setting the contamination warning threshold value of the primary as 1%, setting the buzzer as drop-drop, and setting the sound interval between every two sounds as at least 5S, wherein the warning sound is slow rhythm; regarding the fluorescence contamination area with the proportion of 10-20% as a middle level, setting the contamination warning threshold value of the middle level as 10%, setting the buzzer as drop-drop, and setting the sound interval between every two sounds as at least 3S, wherein the warning sound is a relatively rapid rhythm; regarding the fluorescence contamination area with the proportion of more than 20% as the high level, the contamination warning threshold value of the high level can be set to be 20%, the buzzer is set to be drop-drop, the sound interval in every two sounds is at least 1S, and the warning sound is the ultra-rapid rhythm; the client judges the severity of fluorescent staining after fabric printing and dyeing according to the rhythm of warning sound sent by the buzzer, so that the client is convenient to supervise and prompt to check the fabric in time.
The data storage module is used for storing the processed fabric printing and dyeing fluorescent stain image pictures and the fluorescent stain calculation results according to time sequences; specifically, the detection pictures and the detection results thereof are correspondingly stored, so that the client can check and refer in the later period, and historical data are obtained.
The invention provides a fluorescent staining method for fabric printing and dyeing, which comprises the following steps of:
s1, obtaining a current fabric printing and dyeing fluorescent stain image picture by arranging an area array camera array;
s2, carrying out region division on the current fabric printing and dyeing fluorescent staining image picture, and extracting fabric fluorescent staining regions and fabric fluorescent non-staining regions through different tones;
S3, filtering the fabric printing and dyeing fluorescent stain image pictures after the region division, and eliminating noise in the pictures;
S4, calculating the total area of the fabric printing and dyeing fluorescent staining image picture by adopting a Sobe l algorithm, and then calculating the actual area of a fluorescent staining area in the picture according to the same steps;
S5, calculating the proportion of the actual area of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture;
s6, presetting a duty ratio grade mechanism and a contamination warning threshold value, firstly judging the grade of the current fluorescence contamination area duty ratio, and transmitting the signal to a man-machine interaction platform for display; the man-machine interaction platform compares the current fluorescence contamination duty ratio grade contamination warning threshold value, and sends out warning sound under the condition that the current fluorescence contamination duty ratio grade contamination warning threshold value exceeds the contamination warning threshold value, so that a client is reminded to solve the problem in time.
The beneficial effects achieved by the above contents are that: by the method, the existing fluorescence contamination detection method can avoid the defects of detection personnel in a detection workshop for a long time, and the practicability and safety of the existing fluorescence contamination method are optimized.
Working principle: acquiring a current fabric printing and dyeing fluorescent stain image picture through an area array camera, and carrying out region division and noise reduction treatment on the picture; extracting edge pixels of a fluorescent staining area in the fabric printing and dyeing fluorescent staining image picture by adopting a Sobe l algorithm, and calculating the total area of the fabric printing and dyeing fluorescent staining image picture and the actual area of the fluorescent staining area; judging the proportion of the fluorescent staining area to the total area of the fabric printing and dyeing fluorescent staining image picture and the grade of the fluorescent staining image picture, and sending out warning sound to remind the client to solve the problem in time under the condition that the staining warning threshold value is exceeded.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made hereto without departing from the spirit and principles of the present invention.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411050788.7A CN119006391A (en) | 2024-08-01 | 2024-08-01 | Fluorescent staining system and method for fabric printing and dyeing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411050788.7A CN119006391A (en) | 2024-08-01 | 2024-08-01 | Fluorescent staining system and method for fabric printing and dyeing |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN119006391A true CN119006391A (en) | 2024-11-22 |
Family
ID=93478880
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411050788.7A Pending CN119006391A (en) | 2024-08-01 | 2024-08-01 | Fluorescent staining system and method for fabric printing and dyeing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119006391A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202330297U (en) * | 2011-11-28 | 2012-07-11 | 陕西长岭纺织机电科技有限公司 | Device for automatically detecting texture defects |
| CN112184615A (en) * | 2020-07-04 | 2021-01-05 | 浙江省常山纺织有限责任公司 | Image Processing-Based Fabric Colored Fiber Detection System |
| CN114232261A (en) * | 2021-12-23 | 2022-03-25 | 广东溢达纺织有限公司 | Method for anti-fluorescence staining of various fabrics in one process and post-finishing method for various fabrics |
| CN116298223A (en) * | 2023-03-27 | 2023-06-23 | 中国第一汽车股份有限公司 | Method, device, equipment and storage medium for testing antifouling property of textile |
| CN118241373A (en) * | 2024-05-22 | 2024-06-25 | 常州驰恩机械制造有限公司 | Online fabric defect detection device and method for warp knitting machine |
-
2024
- 2024-08-01 CN CN202411050788.7A patent/CN119006391A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202330297U (en) * | 2011-11-28 | 2012-07-11 | 陕西长岭纺织机电科技有限公司 | Device for automatically detecting texture defects |
| CN112184615A (en) * | 2020-07-04 | 2021-01-05 | 浙江省常山纺织有限责任公司 | Image Processing-Based Fabric Colored Fiber Detection System |
| CN114232261A (en) * | 2021-12-23 | 2022-03-25 | 广东溢达纺织有限公司 | Method for anti-fluorescence staining of various fabrics in one process and post-finishing method for various fabrics |
| CN116298223A (en) * | 2023-03-27 | 2023-06-23 | 中国第一汽车股份有限公司 | Method, device, equipment and storage medium for testing antifouling property of textile |
| CN118241373A (en) * | 2024-05-22 | 2024-06-25 | 常州驰恩机械制造有限公司 | Online fabric defect detection device and method for warp knitting machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112508826B (en) | Printed matter defect detection method | |
| CN117541588B (en) | Printing defect detection method for paper product | |
| US6728593B2 (en) | System for analysis of fabric surface | |
| CN108416766B (en) | Double-side light-entering type light guide plate defect visual detection method | |
| CN105067638B (en) | Tire fetal membrane face character defect inspection method based on machine vision | |
| JP2583146B2 (en) | Top cleanliness inspection method | |
| JP4021366B2 (en) | Image quality analysis method and system for display device | |
| Sun et al. | Real-time automatic detection of weld defects in steel pipe | |
| CN112053376B (en) | Workpiece weld joint identification method based on depth information | |
| CN106886216A (en) | Robot automatic tracking method and system based on RGBD Face datections | |
| CN110570411A (en) | A method and device for detecting mura based on coefficient of variation | |
| CN114549441B (en) | Straw defect detection method based on image processing | |
| CN105572143B (en) | The detection method of rolled material surface periodic defect in calender line | |
| CN108414531A (en) | A kind of fexible film defect detecting device and its detection method based on machine vision | |
| CN107545557A (en) | Egg detecting method and device in excrement image | |
| CN114755236A (en) | System and method for detecting surface defects of electroplated part with revolution curved surface | |
| CN116309447B (en) | Dam slope crack detection method based on deep learning | |
| CN117710266A (en) | Night road visibility monitoring method based on video image | |
| CN102103090A (en) | Device and method for detecting quality of web of carding machine on line based on computer vision | |
| CN118914250B (en) | A sheet metal welding defect intelligent detection method and device based on data feedback | |
| CN119006391A (en) | Fluorescent staining system and method for fabric printing and dyeing | |
| CN112345542A (en) | A method for rapid identification of tunnel face cracks | |
| JP2541735B2 (en) | Method and apparatus for diagnosing coating film deterioration | |
| JPH08145907A (en) | Inspection equipment of defect | |
| JP2015025703A (en) | Evaluation method and evaluation apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |