CN111951236A - Intelligent machine vision recognition system - Google Patents
Intelligent machine vision recognition system Download PDFInfo
- Publication number
- CN111951236A CN111951236A CN202010762461.8A CN202010762461A CN111951236A CN 111951236 A CN111951236 A CN 111951236A CN 202010762461 A CN202010762461 A CN 202010762461A CN 111951236 A CN111951236 A CN 111951236A
- Authority
- CN
- China
- Prior art keywords
- unit
- module
- machine vision
- output
- intelligent machine
- 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
- 238000012545 processing Methods 0.000 claims abstract description 15
- 230000005540 biological transmission Effects 0.000 claims abstract description 8
- 238000012797 qualification Methods 0.000 claims abstract 3
- 238000004364 calculation method Methods 0.000 claims description 24
- 238000012217 deletion Methods 0.000 claims description 6
- 230000037430 deletion Effects 0.000 claims description 6
- 230000002950 deficient Effects 0.000 claims 1
- 238000012163 sequencing technique Methods 0.000 claims 1
- 238000001514 detection method Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 5
- 238000005286 illumination Methods 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000000034 method Methods 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
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
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30242—Counting objects in image
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Development Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Image Analysis (AREA)
Abstract
本发明属于机器视觉识别系统领域，尤其是一种智能的机器视觉识别系统，针对现有的机器视觉系统大多只能对产品进行检测，不能对检测的合格率进行实时统计，同时不能对不合格产品出现的问题进行标记、统计的问题，现提出如下方案，其包括采集模块、处理模块、识别模块和控制模块，所述采集模块与处理模块连接，处理模块与识别模块连接，识别模块与控制模块连接，所述识别模块包括识别单元、判断单元、剔除单元、发送单元、第一统计单元、第二统计单元、标记单元、分类单元，本发明可以对产品的合格率进行实时统计、显示，同时可以对不合格产品的不合格位置出现的次数进行统计、显示，便于直观准确的了解产品质量问题。
The invention belongs to the field of machine vision recognition systems, in particular to an intelligent machine vision recognition system. Most of the existing machine vision systems can only detect products, but cannot perform real-time statistics on the qualified rate of detection, and cannot detect unqualified products in real time. The problem of marking and counting the problems of the product is now proposed as follows, which includes an acquisition module, a processing module, an identification module and a control module, the acquisition module is connected with the processing module, the processing module is connected with the identification module, and the identification module is connected with the control module The identification module includes an identification unit, a judgment unit, a rejection unit, a transmission unit, a first statistical unit, a second statistical unit, a marking unit, and a classification unit. The present invention can perform real-time statistics and display on the qualification rate of products, At the same time, the number of unqualified positions of unqualified products can be counted and displayed, which is convenient for intuitive and accurate understanding of product quality problems.
Description
技术领域technical field
本发明涉及机器视觉识别系统技术领域，尤其涉及一种智能的机器视觉识别系统。The invention relates to the technical field of machine vision recognition systems, in particular to an intelligent machine vision recognition system.
背景技术Background technique
机器视觉系统就是利用机器代替人眼来作各种测量和判断，它是计算机学科的一个重要分支，它综合了光学、机械、电子、计算机软硬件等方面的技术，涉及到计算机、图像处理、模式识别、人工智能、信号处理、光机电一体化等多个领域，机器视觉系统广泛的用于产品检测领域。Machine vision system is to use machines instead of human eyes to make various measurements and judgments. It is an important branch of computer science. It integrates technologies in optics, mechanics, electronics, computer software and hardware, etc. Pattern recognition, artificial intelligence, signal processing, opto-mechanical integration and other fields, machine vision systems are widely used in the field of product inspection.
现有技术中，机器视觉系统大多只能对产品进行检测，不能对检测的合格率进行实时统计，同时不能对不合格产品出现的问题进行标记、统计，因此我们提出了一种智能的机器视觉识别系统，用来解决上述问题。In the prior art, most machine vision systems can only detect products, but cannot perform real-time statistics on the qualified rate of detection, and at the same time, they cannot mark and count the problems of unqualified products. Therefore, we propose an intelligent machine vision system. Identification system is used to solve the above problems.
发明内容SUMMARY OF THE INVENTION
本发明的目的是为了解决现有技术中存在机器视觉系统大多只能对产品进行检测，不能对检测的合格率进行实时统计，同时不能对不合格产品出现的问题进行标记、统计的缺点，而提出的一种智能的机器视觉识别系统。The purpose of the present invention is to solve the shortcomings in the prior art that most machine vision systems can only detect products, cannot perform real-time statistics on the qualified rate of detection, and cannot mark and count the problems of unqualified products at the same time, and An intelligent machine vision recognition system is proposed.
为了实现上述目的，本发明采用了如下技术方案：In order to achieve the above object, the present invention adopts the following technical solutions:
一种智能的机器视觉识别系统，包括采集模块、处理模块、识别模块和控制模块，所述采集模块与处理模块连接，处理模块与识别模块连接，识别模块与控制模块连接，所述识别模块包括识别单元、判断单元、剔除单元、发送单元、第一统计单元、第二统计单元、标记单元、分类单元、分类统计单元、输出单元、计算单元和删除单元，所述识别单元与判断单元连接，判断单元与剔除单元和第一统计单元连接，所述剔除单元和发送单元和第二统计单元连接，所述第二统计单元与标记单元和计算单元连接，所述第一统计单元与计算单元连接，所述计算单元与删除单元和输出单元连接，所述标记单元与分类单元连接，分类单元与分类统计单元连接，分类统计单元与输出单元连接。An intelligent machine vision recognition system includes an acquisition module, a processing module, an identification module and a control module, wherein the acquisition module is connected with the processing module, the processing module is connected with the identification module, and the identification module is connected with the control module, the identification module includes Identification unit, judgment unit, elimination unit, sending unit, first statistics unit, second statistics unit, marking unit, classification unit, classification statistics unit, output unit, calculation unit and deletion unit, the identification unit is connected with the judgment unit, The judging unit is connected to the culling unit and the first statistical unit, the culling unit and the sending unit are connected to the second statistical unit, the second statistical unit is connected to the marking unit and the calculation unit, and the first statistical unit is connected to the calculation unit , the calculation unit is connected with the deletion unit and the output unit, the marking unit is connected with the classification unit, the classification unit is connected with the classification statistics unit, and the classification statistics unit is connected with the output unit.
优选的，所述采集模块包括采集单元、调整单元和照明单元，采集单元与调整单元连接，调整单元与照明单元连接。Preferably, the collection module includes a collection unit, an adjustment unit and an illumination unit, the collection unit is connected to the adjustment unit, and the adjustment unit is connected to the illumination unit.
优选的，所述输出单元包括合格率输出子单元、不合格输出子单元和排序子单元，合格率输出子单元与不合格输出子单元连接，不合格输出子单元与排序子单元连接。Preferably, the output unit includes a pass rate output subunit, a fail output subunit and a sorting subunit, the pass rate output subunit is connected to the fail output subunit, and the fail output subunit is connected to the sorting subunit.
优选的，所述控制模块包括接收单元、控制单元和传输单元，接收单元与控制单元连接，控制单元与传输单元连接。Preferably, the control module includes a receiving unit, a control unit and a transmission unit, the receiving unit is connected with the control unit, and the control unit is connected with the transmission unit.
优选的，所述识别单元用于对图像信息进行识别，并将识别的信息传输至判断单元，判断单元用于对接收的信息数据是否合格作出判断，第一统计单元用于对合格的数量进行统计，并将统计的数量传输至计算单元。Preferably, the identifying unit is used to identify the image information, and transmit the identified information to the judging unit, the judging unit is used to judge whether the received information data is qualified, and the first statistic unit is used to calculate the qualified quantity. Statistics, and the number of statistics is transferred to the calculation unit.
优选的，所述剔除单元用于发送剔除信号，剔除信号经发送单元传输至控制模块，控制模块控制设备将不合格产品剔除。Preferably, the rejecting unit is used for sending a rejecting signal, and the rejecting signal is transmitted to the control module through the sending unit, and the control module controls the equipment to reject the unqualified products.
优选的，所述第二统计单元用于对不合格产品的数量进行统计，并将统计的数据传输至计算单元，计算单元用于根据接收的合格与不合格数量计算出产品的合格率，并将合格率传输至输出单元，输出单元用于对接收的数据进行显示。Preferably, the second statistical unit is used to count the number of unqualified products, and transmit the statistical data to the calculation unit, and the calculation unit is used to calculate the qualified rate of the products according to the received qualified and unqualified quantities, and The pass rate is transmitted to the output unit, which is used to display the received data.
优选的，所述标记单元用于将不合格产品的不合格位置进行标记，并将标记数据传输至分类单元，分类单元根据不同的标记位置对接收的数据进行分类，并传输至分类统计单元，分类统计单元用于对接收的不同类别的数据的数量进行统计，并传输至输出单元，输出单元根据不合格位置出现次数的多少进行排序显示。Preferably, the marking unit is used to mark the unqualified position of the unqualified product, and transmit the marked data to the classification unit, and the classification unit classifies the received data according to different marked positions, and transmits it to the classification and statistics unit, The classification statistics unit is used to count the number of received data of different categories, and transmit it to the output unit, and the output unit sorts and displays the number of occurrences of unqualified positions.
与现有技术相比，本发明的有益效果在于：Compared with the prior art, the beneficial effects of the present invention are:
本方案通过识别单元对图像信息进行识别，并将识别的信息传输至判断单元，通过判断单元对接收的信息数据是否合格作出判断，第一统计单元对合格的数量进行统计，并将统计的数量传输至计算单元；In this scheme, the image information is identified by the identification unit, and the identified information is transmitted to the judgment unit, and the judgment unit judges whether the received information data is qualified. transmitted to the computing unit;
本方案通过剔除单元发送剔除信号，剔除信号经发送单元传输至控制模块，控制模块控制设备将不合格产品剔除，通过第二统计单元对不合格产品的数量进行统计，并将统计的数据传输至计算单元，计算单元根据接收的合格与不合格数量计算出产品的合格率，并将合格率传输至输出单元，通过输出单元对接收的数据进行显示；In this scheme, the rejection signal is sent by the rejection unit, and the rejection signal is transmitted to the control module through the sending unit. The control module controls the equipment to reject the unqualified products, and counts the number of unqualified products through the second statistical unit, and transmits the statistical data to A calculation unit, the calculation unit calculates the qualified rate of the product according to the received qualified and unqualified quantities, and transmits the qualified rate to the output unit, and displays the received data through the output unit;
本方案通过标记单元将不合格产品的不合格位置进行标记，并将标记数据传输至分类单元，分类单元根据不同的标记位置对接收的数据进行分类，并传输至分类统计单元，通过分类统计单元对接收的不同类别的数据的数量进行统计，并传输至输出单元，输出单元根据不合格位置出现次数的多少进行排序显示；In this scheme, the unqualified position of the unqualified product is marked by the marking unit, and the marked data is transmitted to the classification unit. The number of received data of different categories is counted and transmitted to the output unit, and the output unit is sorted and displayed according to the number of occurrences of unqualified positions;
本发明可以对产品的合格率进行实时统计、显示，同时可以对不合格产品的不合格位置出现的次数进行统计、显示，便于直观准确的了解产品质量问题。The present invention can perform real-time statistics and display on the qualified rate of products, and simultaneously can perform statistics and display on the occurrence times of unqualified positions of unqualified products, which facilitates intuitive and accurate understanding of product quality problems.
附图说明Description of drawings
图1为本发明提出的一种智能的机器视觉识别系统的工作原理框图；Fig. 1 is the working principle block diagram of a kind of intelligent machine vision recognition system proposed by the present invention;
图2为本发明提出的一种智能的机器视觉识别系统的识别模块的框图；2 is a block diagram of a recognition module of an intelligent machine vision recognition system proposed by the present invention;
图3为本发明提出的一种智能的机器视觉识别系统的采集模块的框图；3 is a block diagram of a collection module of an intelligent machine vision recognition system proposed by the present invention;
图4为本发明提出的一种智能的机器视觉识别系统的输出单元的框图；4 is a block diagram of an output unit of an intelligent machine vision recognition system proposed by the present invention;
图5为本发明提出的一种智能的机器视觉识别系统的控制模块的框图。FIG. 5 is a block diagram of a control module of an intelligent machine vision recognition system proposed by the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments.
参照图1-5，一种智能的机器视觉识别系统，包括采集模块、处理模块、识别模块和控制模块，采集模块与处理模块连接，处理模块与识别模块连接，识别模块与控制模块连接，识别模块包括识别单元、判断单元、剔除单元、发送单元、第一统计单元、第二统计单元、标记单元、分类单元、分类统计单元、输出单元、计算单元和删除单元，识别单元与判断单元连接，判断单元与剔除单元和第一统计单元连接，剔除单元和发送单元和第二统计单元连接，第二统计单元与标记单元和计算单元连接，第一统计单元与计算单元连接，计算单元与删除单元和输出单元连接，标记单元与分类单元连接，分类单元与分类统计单元连接，分类统计单元与输出单元连接。Referring to Figures 1-5, an intelligent machine vision recognition system includes an acquisition module, a processing module, an identification module and a control module. The acquisition module is connected to the processing module, the processing module is connected to the identification module, the identification module is connected to the control module, and the identification module is connected to the control module. The module includes an identification unit, a judgment unit, a rejection unit, a transmission unit, a first statistical unit, a second statistical unit, a marking unit, a classification unit, a classification statistics unit, an output unit, a calculation unit and a deletion unit, and the identification unit is connected with the judgment unit, The judgment unit is connected with the rejection unit and the first statistical unit, the rejection unit is connected with the sending unit and the second statistical unit, the second statistical unit is connected with the marking unit and the calculation unit, the first statistical unit is connected with the calculation unit, and the calculation unit is connected with the deletion unit It is connected with the output unit, the marking unit is connected with the classification unit, the classification unit is connected with the classification statistics unit, and the classification statistics unit is connected with the output unit.
本发明中，采集模块包括采集单元、调整单元和照明单元，采集单元与调整单元连接，调整单元与照明单元连接。In the present invention, the collection module includes a collection unit, an adjustment unit and an illumination unit, the collection unit is connected with the adjustment unit, and the adjustment unit is connected with the illumination unit.
本发明中，输出单元包括合格率输出子单元、不合格输出子单元和排序子单元，合格率输出子单元与不合格输出子单元连接，不合格输出子单元与排序子单元连接。In the present invention, the output unit includes a pass rate output subunit, a fail output subunit and a sorting subunit, the pass rate output subunit is connected with the fail output subunit, and the fail output subunit is connected with the sorting subunit.
本发明中，控制模块包括接收单元、控制单元和传输单元，接收单元与控制单元连接，控制单元与传输单元连接。In the present invention, the control module includes a receiving unit, a control unit and a transmission unit, the receiving unit is connected with the control unit, and the control unit is connected with the transmission unit.
本发明中，识别单元用于对图像信息进行识别，并将识别的信息传输至判断单元，判断单元用于对接收的信息数据是否合格作出判断，第一统计单元用于对合格的数量进行统计，并将统计的数量传输至计算单元。In the present invention, the identification unit is used to identify the image information, and the identified information is transmitted to the judgment unit, the judgment unit is used to judge whether the received information data is qualified, and the first statistical unit is used to count the qualified quantity. , and transfer the statistics to the calculation unit.
本发明中，剔除单元用于发送剔除信号，剔除信号经发送单元传输至控制模块，控制模块控制设备将不合格产品剔除。In the present invention, the rejecting unit is used for sending the rejecting signal, and the rejecting signal is transmitted to the control module through the sending unit, and the control module controls the equipment to reject the unqualified products.
本发明中，第二统计单元用于对不合格产品的数量进行统计，并将统计的数据传输至计算单元，计算单元用于根据接收的合格与不合格数量计算出产品的合格率，并将合格率传输至输出单元，输出单元用于对接收的数据进行显示。In the present invention, the second statistical unit is used to count the number of unqualified products, and transmit the statistical data to the calculation unit, and the calculation unit is used to calculate the qualified rate of the products according to the received qualified and unqualified quantities, The pass rate is transmitted to the output unit, which is used to display the received data.
本发明中，标记单元用于将不合格产品的不合格位置进行标记，并将标记数据传输至分类单元，分类单元根据不同的标记位置对接收的数据进行分类，并传输至分类统计单元，分类统计单元用于对接收的不同类别的数据的数量进行统计，并传输至输出单元，输出单元根据不合格位置出现次数的多少进行排序显示。In the present invention, the marking unit is used to mark the unqualified position of the unqualified product, and transmit the marked data to the classification unit. The statistic unit is used to count the number of received data of different categories, and transmit it to the output unit, and the output unit will sort and display according to the number of occurrences of unqualified positions.
本发明中，通过采集模块采集图像信息，并将图像信息传输至处理模块，通过处理模块对图像信息进行处理，然后传输至识别模块，通过识别单元对图像信息进行识别，并将识别的信息传输至判断单元，通过判断单元对接收的信息数据是否合格作出判断，第一统计单元对合格的数量进行统计，并将统计的数量传输至计算单元，通过剔除单元发送剔除信号，剔除信号经发送单元传输至控制模块，控制模块控制设备将不合格产品剔除，通过第二统计单元对不合格产品的数量进行统计，并将统计的数据传输至计算单元，计算单元根据接收的合格与不合格数量计算出产品的合格率，并将合格率传输至输出单元，通过输出单元对接收的数据进行显示，通过标记单元将不合格产品的不合格位置进行标记，并将标记数据传输至分类单元，分类单元根据不同的标记位置对接收的数据进行分类，并传输至分类统计单元，通过分类统计单元对接收的不同类别的数据的数量进行统计，并传输至输出单元，输出单元根据不合格位置出现次数的多少进行排序显示。In the present invention, the image information is collected by the acquisition module, and the image information is transmitted to the processing module, the image information is processed by the processing module, and then transmitted to the recognition module, the image information is recognized by the recognition unit, and the recognized information is transmitted. To the judging unit, the judging unit judges whether the received information data is qualified or not, the first statistical unit counts the qualified quantity, and transmits the counted quantity to the calculation unit, sends the culling signal through the culling unit, and the culling signal passes through the sending unit. It is transmitted to the control module, the control module controls the equipment to remove the unqualified products, counts the number of unqualified products through the second statistical unit, and transmits the statistical data to the calculation unit, and the calculation unit calculates according to the received qualified and unqualified quantities. The qualified rate of the product is output, and the qualified rate is transmitted to the output unit, the received data is displayed through the output unit, the unqualified position of the unqualified product is marked by the marking unit, and the marked data is transmitted to the classification unit, the classification unit The received data is classified according to different marking positions, and transmitted to the classification and statistics unit. The number of received data of different categories is counted by the classification and statistics unit, and transmitted to the output unit. The output unit is based on the number of occurrences of unqualified positions. How many to sort display.
以上所述，仅为本发明较佳的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，根据本发明的技术方案及其发明构思加以等同替换或改变，都应涵盖在本发明的保护范围之内。The above description is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited to this. The equivalent replacement or change of the inventive concept thereof shall be included within the protection scope of the present invention.
Claims (8)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010762461.8A CN111951236A (en) | 2020-07-31 | 2020-07-31 | Intelligent machine vision recognition system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010762461.8A CN111951236A (en) | 2020-07-31 | 2020-07-31 | Intelligent machine vision recognition system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111951236A true CN111951236A (en) | 2020-11-17 |
Family
ID=73339135
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010762461.8A Pending CN111951236A (en) | 2020-07-31 | 2020-07-31 | Intelligent machine vision recognition system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111951236A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114565868A (en) * | 2022-02-16 | 2022-05-31 | 易唯思智能自动化装备无锡有限公司 | A product inspection system based on machine vision analysis |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305950A (en) * | 2011-04-29 | 2012-01-04 | 无锡众望四维科技有限公司 | Method for automatically detecting missed accessory during automatic assembly of injector by using machine visual system |
| US20160117553A1 (en) * | 2013-06-07 | 2016-04-28 | Zte Corporation | Method, device and system for realizing visual identification |
| CN107024478A (en) * | 2017-04-05 | 2017-08-08 | 合肥德仁智能科技有限公司 | A kind of part processes automatic defect identifying system |
| CN108872247A (en) * | 2018-06-15 | 2018-11-23 | 南京吉目希自动化科技有限公司 | A kind of product automatic checkout system and detection method based on machine vision and RFID |
| CN109916913A (en) * | 2019-04-04 | 2019-06-21 | 哈尔滨理工大学 | A machine vision-based intelligent manufacturing product identification and detection method |
-
2020
- 2020-07-31 CN CN202010762461.8A patent/CN111951236A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305950A (en) * | 2011-04-29 | 2012-01-04 | 无锡众望四维科技有限公司 | Method for automatically detecting missed accessory during automatic assembly of injector by using machine visual system |
| US20160117553A1 (en) * | 2013-06-07 | 2016-04-28 | Zte Corporation | Method, device and system for realizing visual identification |
| CN107024478A (en) * | 2017-04-05 | 2017-08-08 | 合肥德仁智能科技有限公司 | A kind of part processes automatic defect identifying system |
| CN108872247A (en) * | 2018-06-15 | 2018-11-23 | 南京吉目希自动化科技有限公司 | A kind of product automatic checkout system and detection method based on machine vision and RFID |
| CN109916913A (en) * | 2019-04-04 | 2019-06-21 | 哈尔滨理工大学 | A machine vision-based intelligent manufacturing product identification and detection method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114565868A (en) * | 2022-02-16 | 2022-05-31 | 易唯思智能自动化装备无锡有限公司 | A product inspection system based on machine vision analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110110613B (en) | A method for detecting abnormal persons in rail transit based on motion recognition | |
| CN100506401C (en) | Pearl real-time detection and grading system based on machine vision | |
| CN101566582B (en) | Medicine bottle label information online detection system in powder injection production based on mechanical vision | |
| CN101696945A (en) | On-line detection method of machine vision system to photovoltaic glass flaws | |
| CN102095733B (en) | Machine vision-based intelligent detection method for surface defect of bottle cap | |
| CN204479490U (en) | A kind of laser marking On-line Product testing and analysis system | |
| CN103170459B (en) | Spectacle lens flaw detection system | |
| CN109454006A (en) | Chemical fiber wire ingot is stumbled the device and its detection stage division of a defect on-line checking and classification | |
| CN101509766B (en) | On-line detecting method for spring end plane angle by machine vision system | |
| CN109550712A (en) | A kind of chemical fiber wire tailfiber open defect detection system and method | |
| CN104614380A (en) | Plate-strip surface quality detection system and method | |
| CN113744244B (en) | Online visual inspection system for measuring the distance from the edge of the lithium battery pole piece to the edge of the tab | |
| CN114565868A (en) | A product inspection system based on machine vision analysis | |
| CN102157024B (en) | System and method for on-line secondary detection checking of checking data of large-sheet checking machine | |
| CN102236925B (en) | System and method for offline secondary detection and checking of machine detected data of large-piece checker | |
| CN113834814A (en) | Glove surface defect detection device | |
| CN206132657U (en) | Gilt quality intelligent detecting system based on machine vision | |
| CN101696943B (en) | On-line detection method of machine vision system to medical surgical knife flaws | |
| CN101565109A (en) | Aluminum cap packaging online detection system in medical powder injection production based on mechanical vision | |
| CN114549493A (en) | A deep learning-based magnetic core defect detection system and method | |
| CN104132945A (en) | On-line surface quality visual inspection device for bar based on optical fiber conduction | |
| CN101696877A (en) | On-line detection method of machine vision system to spring verticality | |
| CN109726730A (en) | Automatic optical inspection image classification method, system and computer readable medium | |
| CN114494103A (en) | Defect detection method and device | |
| CN203245133U (en) | Lens defect detecting system |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201117 |
|
| RJ01 | Rejection of invention patent application after publication |