CN101778188B - Method for beautifying faces in digital image - Google Patents
Method for beautifying faces in digital image Download PDFInfo
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- CN101778188B CN101778188B CN 200910001234 CN200910001234A CN101778188B CN 101778188 B CN101778188 B CN 101778188B CN 200910001234 CN200910001234 CN 200910001234 CN 200910001234 A CN200910001234 A CN 200910001234A CN 101778188 B CN101778188 B CN 101778188B
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000001914 filtration Methods 0.000 claims description 14
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical class C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 claims description 6
- YTAHJIFKAKIKAV-XNMGPUDCSA-N [(1R)-3-morpholin-4-yl-1-phenylpropyl] N-[(3S)-2-oxo-5-phenyl-1,3-dihydro-1,4-benzodiazepin-3-yl]carbamate Chemical compound O=C1[C@H](N=C(C2=C(N1)C=CC=C2)C1=CC=CC=C1)NC(O[C@H](CCN1CCOCC1)C1=CC=CC=C1)=O YTAHJIFKAKIKAV-XNMGPUDCSA-N 0.000 claims description 5
- 230000001815 facial effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 13
- 238000003672 processing method Methods 0.000 description 5
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 description 4
- 210000000887 face Anatomy 0.000 description 4
- 239000011148 porous material Substances 0.000 description 4
- 206010027146 Melanoderma Diseases 0.000 description 3
- 208000003351 Melanosis Diseases 0.000 description 3
- 230000006378 damage Effects 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000010612 desalination reaction Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 210000000720 eyelash Anatomy 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 210000004209 hair Anatomy 0.000 description 1
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Abstract
The invention discloses a method for beautifying faces in a digital image, which carries out beautifying processing on a facial region of an input image. The method comprises the following steps: setting a selection window for selecting part image regions of the input image; assigning a target pixel from the selection window and assigning the rest of pixels as comparison pixels; performing a detail test program according to a variation amount of the target pixel to the comparison pixels and judging whether the target pixel has detailed information or not; performing a brightness test program on the target pixel and judging whether the target pixel corresponds to a brightness region or not; performing a nonlinearity filtering program, processing the target pixel by a nonlinearity filter to generate a filter value, providing a mixing proportion and mixing the target pixel and the filter value in the mixing proportion to generate a completed pixel; replacing the original target pixel with the completed pixel; and repeating the steps until all the pixels are completed.
Description
Technical field
The present invention relates to a kind of digital image processing method, be particularly to the method for beautifying faces in a kind of digital picture.
Background technology
Along with the development of digital camera, so that photography no longer is expensive consumption.The user can be random the desired image of shooting, in order to record memorable a moment or scene.Especially take especially many cameramans' one of emphasis of personage.In the process of taking, the person taken picture is perhaps because the factors such as spot, dust or microgroove on the face affect the reader to the impression of captured digital picture.
For solving this problem, although can utilize digital video editing software to come digital picture is carried out the editor of thin section.But be not that general user is familiar to image editing software, therefore cause the raising of user's the ABC of door yet.Another kind of mode is to utilize the softening that improves image, although above-mentioned color lump partly can be diluted like this.But soften handled is processed for the integral body of digital picture.Therefore also can be by soften handled for the place that does not need in the digital picture to adjust.So, cause the impression of digital picture to reduce.
Summary of the invention
In view of above problem, main purpose of the present invention is to provide the method for beautifying faces in a kind of digital picture, in order to the noise (freckle, blackspot, pore or microgroove) on people's face skin of eliminating input picture.
For reaching above-mentioned purpose, the method for beautifying faces in a kind of digital picture disclosed in this invention, in order to the noise on people's face skin of an input picture is eliminated, this colour of skin processing method may further comprise the steps:
A. the partial image region of selecting this input picture is with as a selected window;
B. from this selected window, assign an object pixel, and rest of pixels is assigned as a comparison pixels;
C. according to this object pixel the amount of variability of those comparison pixels is carried out a detail inspection program, whether have a detailed information in order to judge this object pixel;
When d. if this object pixel has this detailed information, then this object pixel is carried out a brightness check problem, judge whether this object pixel is positioned at a brightness section;
If e. this object pixel is positioned at this brightness section, then carry out a non-linear filtration program, this object pixel is produced at least one filter value by a nonlinear filter, one group of mixed proportion is provided again, according to this mixed proportion in order to this object pixel is mixed with this filter value, finished pixel in order to produce one, and this has been finished original this object pixel of pixel replacement; And
F. repeating step a ~ step e, until finish till all pixels in this input picture, and export a target image.
The invention provides a kind of processing method to skin color in the digital picture, in order to the noise of non-skin color is removed.And the pixel arround utilizing is repaired, and except reaching the purpose of beautifying picture, also can reduce the destruction to former figure.
Relevant characteristics and implementation of the present invention cooperate diagram to be described in detail as follows as most preferred embodiment hereby.
Description of drawings
Fig. 1 is operation workflow schematic diagram of the present invention;
Fig. 2 is the operation workflow schematic diagram of step c;
Fig. 3 is the operation workflow schematic diagram of brightness check problem;
Fig. 4 is the operation workflow schematic diagram of non-linear filtration program;
Fig. 5 is the schematic diagram of the object pixel in different bouts;
Fig. 6 implements the operation workflow schematic diagram of aspect for another.
Wherein, Reference numeral:
510 selected window
Embodiment
The method disclosed in the present can apply to have the electronic installation of image-capable, electronic installations such as personal computer, digital camera, digital frame.But should be noted, method of the present invention is non-to only limit to above-mentioned example, only chats first bright at this.And for clearly demonstrating technological means of the present invention, therefore at this each noun below definition.
Input picture P, it is the image of x*y pixel array sized; Selected window, it is the m*n pel array, wherein m and n are positive integer, in enforcement aspect of the present invention take the selected window of 5*5 as example, its non-restriction of the present invention, the Pixel arrangement in the selected window please refer to shown in the table one, and Pn is n position in the selected window; In this implementation take P12 for as object pixel.
| P0 | P1 | P2 | P3 | P4 |
| P5 | P6 | P7 | P8 | P9 |
| P10 | P11 | P12 | P13 | P14 |
| P15 | P16 | P17 | P18 | P19 |
| P20 | P21 | P22 | P23 | P24 |
Table one. selected window
Please refer to shown in Figure 1ly, it is operation workflow schematic diagram of the present invention.The present invention includes following steps:
Step a. sets selected window, and it is in order to select the partial image region of input picture;
Step b. assigns object pixel from selected window, and rest of pixels is assigned as comparison pixels;
Step c is carried out the detail inspection program according to object pixel to the amount of variability of comparison pixel, whether has detailed information in order to judge object pixel;
Steps d. when if object pixel has detailed information, the object pixel in the selected window is carried out the brightness check problem, judge whether object pixel meets brightness section;
When if step e. object pixel meets among the brightness section, carry out the non-linear filtration program, object pixel is produced at least one filter value by nonlinear filter, one group of mixed proportion is provided again, according to mixed proportion in order to object pixel is mixed with filter value, finished pixel in order to produce, and will finish pixel and replace original object pixel;
Step f. judges whether to finish all pixels in the input picture, if do not finish then repeating step a～step e, until finish till all pixels in the input picture, and the export target image; And
Step g. determine whether to continue to carry out colour of skin processing method (meaning is execution in step a～step f).
In step c, steps d and step e, more comprise separately function mode in the present invention.Please refer to shown in Figure 2ly, it is the operation workflow schematic diagram of step c.Whether the detail inspection program has the details of image in order to detect object pixel, wherein the details of image is the pixel of person taken picture's the non-skin such as hair, eyelashes, glasses or earrings.In step c, more may further comprise the steps:
Step c-1. provides the amount of variability threshold value;
Step c-2. is according to object pixel and those comparison pixels calculated level amounts of variability SAD_H;
Step c-3. calculates vertical amount of variability SAD_V according to object pixel with those comparison pixels;
Step c-4. calculates one group of diagonal angle amount of variability SAD_D1, SAD_D2 according to object pixel and those comparison pixels;
Step c-5. calculates total amount of variability SAD according to horizontal amount of variability SAD_H, vertical amount of variability SAD_V and those diagonal angles amount of variability SAD_D1, SAD_D2;
If the total amount of variability SAD of step c-6. judges that then object pixel does not have this detailed information, and choose another pixel and execution in step a from input picture less than the amount of variability threshold value; And
If the total amount of variability SAD of step c-7. judges that then object pixel has this detailed information, and choose another pixel and execution in step a from input picture greater than the amount of variability threshold value.
At the horizontal amount of variability SAD_H of step c-2, it is produced by formula 1:
SAD_H=|P2-P3|+|P7-P8|+|P12-P13|+|P17-P18|+|P22-P23| (formula 1)
At the vertical amount of variability SAD_V of step c-3, it is produced by formula 2:
SAD_V=|P5-P10|+|P6-P11|+|P7-P12|+|P8-P13|+|P9-P14| (formula 2)
At one group of diagonal angle amount of variability SAD_D1, SAD_D2 of step c-4, it is produced by formula 3:
SAD_D1＝|P1-P5|+|P7-P11|+|P13-P17|+|P19-P23|
SAD_D2＝|P3-P9|+|P7-P13|+|P11-P17|+|P15-P21|
(formula 3)
At total amount of variability SAD of step c-5, it is produced by formula 4:
SAD＝SAD_H+SAD_V+SAD_D1+SAD_D2
(formula 4)
As total amount of variability SAD during less than the amount of variability threshold value, then represent this object pixel and do not contain details.
Then, the brightness check problem is in order to filter out the object pixel that meets in the brightness section, and its main purpose is in order to check whether object pixel is freckle, blackspot, pore or microgroove.
More may further comprise the steps before the brightness check problem of execution in step d, please refer to shown in Figure 3ly, it is the operation workflow schematic diagram of brightness check problem:
Steps d-1. is according to the value of object pixel and comparison pixels, in order to computation of mean values Mean;
Steps d-average upper limit value M ean_THU and average value lower limit value Mean_THL 2. are provided, and average value lower limit value Mean_THL is greater than average upper limit value M ean_THU; And
Steps d-3. according to average upper limit value M ean_THU and average value lower limit value Mean_THL, in order to set the scope of brightness section.
In steps d-1. according to following formula 5 computation of mean values Mean:
Wherein, Pi is i position in selected window.
If the brightness of object pixel falls within the brightness section (meaning is the brightness＜average value lower limit value Mean_THL of average upper limit value M ean_THU＜object pixel), then object pixel is freckle, blackspot, pore or microgroove.
Then, please refer to shown in Figure 4ly, it is the operation workflow schematic diagram of non-linear filtration program.In producing filter value, more may further comprise the steps:
Step e-1. is by selecting max pixel value in the comparison pixels, and it is defined as filtering maximum P_Max;
Step e-2. is by selecting intermediate value in the comparison pixels, and it is defined as filtering intermediate value P_Mid; And
Step e-3. in order to filtering maximum P_Max, filtering intermediate value P_Mid are mixed with object pixel, has finished pixel in order to produce according to mixed proportion.
Wherein, according to formula 6 and formula 7 calculation of filtered maximum P_Max and filtering intermediate value P_Mid:
P_Max=max (P
0, P
1, P
2..., P
24) (formula 6)
P_Mid=median (P
0, P
1, P
2..., P
24) (formula 7)
Then, according to mixed proportion in order to filtering maximum P_Max, filtering intermediate value P_Mid are mixed with object pixel.Be respectively constant a, constant b and constant c in this definition mixed proportion, and a+b+c=1.Please refer to shown in (formula 8), it is to utilize output nonlinear filtering result to replace former object pixel again:
P
12=a * P_Max+b * P_Mid+c * P
12(formula 8)
So, process the color desalination speed that to accelerate a time object pixel in the colour of skin of carrying out time bout.This is because the brightness value of the object pixel in front bout was changed, so the object pixel in the new bout will be brought the object pixel of front bout into calculating.Please refer to shown in Figure 5ly, it is the schematic diagram of the object pixel in different bouts.Left at Fig. 5 is the colour of skin processing (the dotted line frame represents selected window 510) of first leg, and right-hand is the colour of skin processing of second leg.When the colour of skin of first leg is processed, can produce the brightness value that replaces former object pixel according to nonlinear filtering result (meaning is the P` (2,2) of selected window 510 among Fig. 5).Therefore in second leg, the pixel brightness value of (2,2) can become P` (2,2) in the position.
In step g, can be by user or the number of times that determines to want to carry out colour of skin processing according to the size of input picture and selected window 510.For instance, if selected window is less or input picture hour, can set the colour of skin of less bout number of times and process, vice versa.Every process through colour of skin after, can reduce the noise of non-skin color in the input picture.
Except above-mentioned enforcement aspect, the present invention more provides another embodiment.Please refer to shown in Figure 6ly, it is the operation workflow schematic diagram of another embodiment.This embodiment may further comprise the steps:
Step a. sets selected window, and it is in order to select the partial image region of input picture;
Step b. assigns object pixel from selected window, and rest of pixels is assigned as comparison pixels;
Step c is carried out the detail inspection program according to object pixel to the amount of variability of comparison pixel, whether has detailed information in order to judge object pixel;
Steps d. when if object pixel has detailed information, the object pixel in the selected window is carried out the brightness check problem, judge whether this object pixel is positioned among the brightness section;
When if step e. object pixel is positioned among the brightness section, carry out the non-linear filtration program, object pixel is produced at least one filter value by nonlinear filter, one group of mixed proportion is provided again, according to mixed proportion in order to object pixel is mixed with filter value, finished pixel in order to produce, and will finish pixel and replace original object pixel;
Step f. judges whether to finish all pixels in the input picture, if not yet finish then repeating step a ~ step e, until finish till all pixels in the input picture, and the export target image;
Step g. judge whether to continue to carry out colour of skin manner of execution, if do not continue then execution in step a ~ step f, produce another target image;
Step h. sets the comparison window, in order to choosing the partial image region in the target image, and assigns an object pixel from the comparison window, and rest of pixels is defined as comparison pixels;
Step I. carry out the detail inspection program, according to the amount of variability of object pixel to the comparison pixel, in order to detect the object pixel with detailed information;
Step j. carries out filter to the object pixel with detailed information, finishes pixel in order to output; And
Step k. judges whether to finish all pixels in the target image, if do not finish then repeating step h～step j, until finish till the pixels all in the target image, and image is finished in output.
Step a～step g is all identical with last embodiment in the present embodiment, and step h is identical with step c and steps d respectively with the detailed practice of step I, so do not add to give unnecessary details at this.The present embodiment is different from the filter that last embodiment difference is step j.Process according to the object pixel in 9 pairs of comparisons of formula window at step j:
Wherein, WOI is the comparison window; (x, y) is the coordinate position of pixel in the comparison window; TH is the filtering threshold value; N compares satisfying condition in the window for this reason | P (i, j) P (x, y) | and the sum of＜TH.
Be in harmonious proportion in order to the skin color in the digital picture is done further for step h～step I, and erase and have the pixel of pore and microgroove.Thus, can be so that the face in the digital picture seems more soft and graceful and level and smooth.
The invention provides a kind of processing method to skin color in the digital picture, in order to the noise of non-skin color is removed.And the pixel arround utilizing is repaired, and except reaching the purpose of beautifying picture, also can reduce the destruction to former figure.
Claims (7)
1. the method for beautifying faces in the digital picture, in order to the noise on people's face skin of an input picture is eliminated, this method for beautifying faces may further comprise the steps:
A. the partial image region of selecting this input picture is with as a selected window;
B. from this selected window, assign an object pixel, and rest of pixels is assigned as a comparison pixels;
C-1., one amount of variability threshold value is provided;
C-2. calculate a horizontal amount of variability SAD_H according to this object pixel and those comparison pixels, wherein, SAD_H=|P2-P3|+|P7-P8|+|P12-P13|+|P17-P18|+|P22-P23|, Pn are n position in the selected window, and n is [1,24];
C-3. calculate a vertical amount of variability SAD_V according to this object pixel with those comparison pixels, wherein,
SAD_V＝|P5-P10|+|P6-P11|+|P7-P12|+|P8-P13|+|P9-P14|.
C-4. calculate one group of diagonal angle amount of variability SAD D1, SAD_D2 according to this object pixel and those comparison pixels, wherein,
SAD_D1=|P1-P5|+|P7-P11| ten | P13-P17|+|P19-P23|,
SAD_D2＝|P3-P9|+|P7-P13|+|P11-P17|+|P15-P21|；
C-5. calculate a total amount of variability SAD according to this horizontal amount of variability SAD_H, this vertical amount of variability SAD_V and those diagonal angles amount of variability SAD_D1, SAD_D2, wherein,
SAD=SAD_H+SAD_V+SAD_D1 and SAD_D2.
If c-6. this total amount of variability SAD is less than this amount of variability threshold value, judge that then this object pixel does not have a detailed information, from this input picture, choose another pixel and execution in step a;
If c-7. this total amount of variability SAD is greater than this amount of variability threshold value, judge that then this object pixel has this detailed information, then from this input picture, choose another pixel and execution in step a;
When d. if this object pixel has this detailed information, then this object pixel is carried out a brightness check problem, judge whether this object pixel is positioned at a brightness section;
If e. this object pixel is positioned at this brightness section, then carry out a non-linear filtration program, this object pixel is produced at least one filter value by a nonlinear filter, one group of mixed proportion is provided again, according to this mixed proportion in order to this object pixel is mixed with this filter value, finished pixel in order to produce one, and this has been finished original this object pixel of pixel replacement; And
F. repeating step a～step e, until finish till all pixels in this input picture, and export a target image;
In step a, arranging of this selected window is as shown in the table:
2. the method for beautifying faces in the digital picture as claimed in claim 1 is characterized in that, this selected window is the m*n pel array, and wherein m and n are positive integer.
3. the method for beautifying faces in the digital picture as claimed in claim 1 is characterized in that, and is further comprising the steps of before steps d:
According to the value of this object pixel and those comparison pixels, in order to calculate an average Mean;
Provide an average upper limit value M ean THU and an average value lower limit value Mean_THL, and this average value lower limit value Mean THL is greater than this average upper limit value M ean_THU; And
According to this average upper limit value M ean THU and this average value lower limit value Mean_THL, in order to set the scope of this brightness section.
4. the method for beautifying faces in the digital picture as claimed in claim 1 is characterized in that, those filter values of the generation in step e are further comprising the steps of:
By selecting max pixel value in those comparison pixels, and it is defined as a filtering maximum P_Max;
By selecting intermediate value in those comparison pixels, and it is defined as a filtering intermediate value P_Mid; And
In order to this filtering maximum P_Max, this filtering intermediate value P_Mid are mixed with this object pixel, finished pixel in order to produce this according to this mixed proportion.
5. the method for beautifying faces in the digital picture as claimed in claim 1 is characterized in that, and is further comprising the steps of behind this step f:
Determine whether to proceed step a～step f.
6. the method for beautifying faces in the digital picture as claimed in claim 5 is characterized in that, and is further comprising the steps of after finishing deciding step:
H. set a comparison window, in order to choosing the partial image region in this target image, and from this comparison window, assign this object pixel, rest of pixels is defined as those comparison pixels;
I. carry out this detail inspection program, according to the amount of variability of this object pixel to those comparison pixels, in order to detect this object pixel with this detailed information;
J. this object pixel with this detailed information is carried out a filter, finish pixel in order to export one; And
K. repeating step h～step j, until finish till the pixels all in this target image, and export one and finish image.
7. the method for beautifying faces in the digital picture as claimed in claim 6, wherein further comprising the steps of in step I:
If this object pixel does not detect when having this detailed information, then from this target image, choose another pixel, and repeated execution of steps h.
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| CN103905707A (en) * | 2012-12-24 | 2014-07-02 | 腾讯科技（深圳）有限公司 | Method and device for controlling image pickup device |
| CN103761536B (en) * | 2014-01-28 | 2017-03-22 | 五邑大学 | Human face beautifying method based on non-supervision optimal beauty features and depth evaluation model |
| CN105469017B (en) * | 2014-06-26 | 2019-09-10 | 小米科技有限责任公司 | Face image processing process and device |
| CN104469253A (en) * | 2015-01-05 | 2015-03-25 | 掌赢信息科技（上海）有限公司 | Face beautification method in real-time video and electronic equipment |
| CN107392099B (en) * | 2017-06-16 | 2020-01-10 | Oppo广东移动通信有限公司 | Method and device for extracting hair detail information and terminal equipment |
| CN108986018B (en) * | 2018-07-02 | 2019-05-10 | 上海蒙彤文化传播有限公司 | Automatic U.S. figure platform based on the beautification of the face cheek |
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| CN1659794A (en) * | 2002-05-01 | 2005-08-24 | 汤姆森特许公司 | Deblocking filter adjusted according to pixel brightness |
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