CN104732200B - A kind of recognition methods of skin type and skin problem - Google Patents
A kind of recognition methods of skin type and skin problem Download PDFInfo
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Abstract
The present invention relates to technical field of face recognition, the recognition methods of more particularly to a kind of skin type and skin problem, it comprises the following steps successively：Obtain facial image；Detect whether the facial image includes face；Detect skin colour and colourity；Calculate texture comparison's angle value；Calculate average gray；And above-mentioned calculating acquired results are matched with the presetting database, and the skin problem result obtained by output matching.The recognition methods of the present invention assigns the ability of the subject's skin type and skin problem in computer analysis facial image, realize automatic intelligent management, and subject's skin is analyzed, some indexs such as the colour of skin, spot, moisture oil content, texture wrinkle and pore are drawn, overall merit is carried out to skin surface situation.
Description
Technical field
The present invention relates to technical field of face recognition, the recognition methods of more particularly to a kind of skin type and skin problem.
Background technology
Face is one of important biological characteristic, and substantial amounts of information, such as sex, age, people have been contained on facial image
Kind, identity etc..The development of human-computer interaction technology (HCI) causes computer vision, artificial intelligence, is set in monitoring, GUI man-machine interfaces
Meter etc. plays an increasingly important role.With advances in technology, also turn near based on facial image pattern recognition problem
The focus studied over year.Including Face datection, face identification, face character (sex, age, expression, race etc.)
All kinds of identification problems such as identification.
With the development of modern society, people are to the healthy requirement of autologous skin also more and more higher.It is convenient rapidly to help
User finds oneself skin type and skin problem and just seems more significant.The present invention can be adopted by mobile device terminal
Collect user's human face photo, photo is analyzed by intelligent skin identifying system, and result is fed back into user.
Chinese patent application CN 102831408A disclose a kind of face identification method, and it comprises the following steps：S1 judges
Detect in video sequence with the presence or absence of the certain gestures of user's setting；If so, carry out S2；Otherwise, repeat step S1；S2 detections regard
Whether user face is had in frequency section, if so, carrying out step S3, otherwise repeat step S2；S3 enters to the user's face detected
Row real-time tracking；S4 extracts illumination-insensitive feature to user's facial image；S5 analog subscriber postural change rules；S6 faces are known
Other process, judges whether facial image to be identified belongs to a people together with the sample in face database, if so, identification process terminates, is
System performs user's operation；If it is not, carry out step S7；S7 asks the user whether it is to use system for the first time；If so, newly-built sample
Storehouse, if it is not, ask the user whether to substitute Sample Storehouse, if so, user's facial image is replaced into original sample in face database, it is no
Then end operation.
From the prior art, it will also be appreciated that：The A of Chinese patent application CN 103729625, which disclose a kind of face, to be known
Method for distinguishing, and the A of Chinese patent application CN 103761504 disclose a kind of face identification system.
However, above-mentioned prior art can only provide the system or method of a kind of recognition of face, can not further utilize
Face image data, there is provided more detailed analyzing and processing, such as the sex to user, skin, face characteristic similarity, Yi Jinian
The analytic function in age etc., to cater to the particular demands of user.
The content of the invention
For overcome the deficiencies in the prior art, the present invention provides a kind of recognition methods of skin type and skin problem, and it is special
Part is not to comprise the following steps successively：
S1, use camera device acquisition facial image；
S2, detect whether the facial image includes face, and when it is determined that the facial image includes face, jump procedure
S3；
S3, it is to facial image progress skin colour and colorimetric detection, the calculation formula of the wherein detection：
Wherein, M, N are the two-dimensional of image, and i, j represent the row, column of the place image of the pixel respectively, and c is described
The value of the color component of pixel；
S4, a texture co-occurrence matrix C (i, j) is defined, and calculated using below equation and obtain texture comparison's angle value：
S5, the gray value Fast Match Algorithm using sum of squares of deviations method and the facial image, obtain following calculation formula：
Wherein, E (Si,j) with E (T) be user's skin subgraph S respectivelyi,jWith the gray scale of the skin image T in presetting database
Average value；
S6, abovementioned steps S3 to S5 calculating acquired results are matched with the pre-set skin issue database, and exported
Match the skin problem result of gained.
According to one embodiment of present invention, before the recognition methods is implemented, initially set up comprising various typical faces
Skin image storehouse.
According to one embodiment of present invention, step S2 utilizes network neural method, character references method or primary standard of color method
To detect whether the facial image includes face.
According to one embodiment of present invention, before step S3 is performed, photo-irradiation treatment is performed to the facial image,
The facial image is changed using histogram specification, wherein the calculation formula of the conversion is：
Wherein, f (x, y) is the pixel element data of input facial image, and g (x, y) is the picture of output gray level histogram
Vegetarian refreshments element data, a, b, c are the location and shape and the parameter that introduces for adjusting curve.Further, by the facial image
After being changed using histogram specification, then 3 × 3 medium filterings are carried out, remove the noise information introduced in image.
Pass through above-mentioned technical proposal, it can be realized according to the recognition methods of the skin type of the present invention and skin problem following
Technique effect：
(1) ability of the subject's skin type and skin problem in computer analysis facial image is assigned；
(2) automatic intelligent management is realized
(3) subject's skin is analyzed, draws some fingers such as the colour of skin, spot, moisture oil content, texture wrinkle and pore
Mark, overall merit is carried out to skin surface situation.
Brief description of the drawings
Fig. 1 shows the method flow diagram of identification skin type according to embodiments of the present invention and skin problem.
Fig. 2 shows the another method flow chart of identification skin type according to embodiments of the present invention and skin problem.
Embodiment
Describe the present invention in detail below in conjunction with accompanying drawing and specific implementation method, the present invention schematic implementation and
Illustrate for explaining the present invention, but it is not as a limitation of the invention.
Before recognition methods according to embodiments of the present invention is implemented, the skin for including various typical faces can be pre-established
Skin image library.The research and experiment of current most of face aspect problem are all based on one or several facial image databases to enter
Capable.In order to realize the research of face skin type and skin problem recognizer and practical, can establish for realizing people
The universal standard facial image database of face skin type and the recognizer of skin problem, the image in the image library is in shooting condition
On have certain limitation, for example the size for face must constrain in some defined scope, the ash of different illumination conditions
Facial image is spent, and has strictly divided training set, storehouse (Gallery), different test set etc., this is field of face identification
One of most widely used face database.
As illustrated in fig. 1 and 2, after facial image is obtained by camera device, the image obtained is carried out first pre-
Processing, include validating that face, face pretreatment.
In the present embodiment, confirming the method for face may include：Network neural method (Neural Network), character references
The method of method (Feature-based) and primary standard of color method (Color-based).Wherein, network neural method uses many
Training set data (Training Data) goes training network neural, and these data somes are that face, some are non-faces
, enable a system to pick out the image comprising face.Character references method is to detect face using some features of face,
Such as：Eyes, nose, face on face, and these organs have fixed relative position；And for whole face, greatly
It is generally oval, and edge line substantially, etc. is had between face and background, these features is available for systems scan and goes out people
Face.And primary standard of color rule is to judge whether certain image includes face using the color of face：It is well known that the face of face
Color generally includes the color such as orange, yellow, white, brown, dark brown；If image is GTG, the change of the gray scale color of face
Can't be too big, and eyes, face, hair are more black parts；Thus, according to organs such as eyes, eyebrow, face, noses
Feature and mutual geometry site, can detect face.
Detect in the image comprising after face, it usually needs the image is pre-processed, because pending
Facial image be frequently present of the problem of uneven illumination is even, and this can directly influence the feature extraction precision of face, therefore right
The image of input must carry out photo-irradiation treatment to improve picture quality.Usually, grey level histogram can be used for representing digital picture
In statistical relationship between each gray level and its frequency occurred.For it is partially dark, partially bright, brightness range is insufficient or contrast
The image of deficiency carries out histogram specification, and the histogram distribution of input picture can be caused to be transformed into approximate specific Nogata
Figure.Transforming function transformation function can select the function of the form such as Gauss, Rayleigh, logarithm, index.Become in the present embodiment using logarithm
Change form：
In formula, f (x, y) is input picture, and g (x, y) is output image, a, b, c be adjust curve location and shape and
The parameter of introducing.By this conversion the low tonal range of image can be enable to extend, high tonal range can be compressed, image
Intensity profile tend to be uniform.Preferably, carry out such as 3 × 3 medium filtering again to the image after greyscale transformation, remove image
The noise information of middle introducing, to improve picture quality.
After extracting face characteristic, using method according to embodiments of the present invention to obtain required skin type/problem
Required output result, including：Detect skin colour and colourity, calculate texture comparison's angle value, calculating average gray and will be upper
Calculating acquired results are stated to be matched with the presetting database, and the skin problem result obtained by output matching.
In the present embodiment, can using such a algorithm to detect skin colour and colourity, wherein, with skin color
The colour of matrix/color intensity distribution is characterized to characterize a colorized face images.Most distribution of color information can be by three
Individual second-order matrix represents, wherein, what a line rank matrix (μ c) characterized is average color, and what two wires rank matrix (δ c) characterized is mark
Quasi- deviation, and third moment sign is degree of skewness (θ c) color.Using following mathematical formulae, from these three low order matrixes (μ
C, δ c, θ C) each three kinds of color planes (R, G, B) of extraction：
Wherein, M, N are the two-dimensional of image, and i, j represent the place row, column of the pixel respectively, and c is color component
Value.The result is that, it is only necessary to extract feature of nine parameters as colorized face images, for example, including color plane parameter (RGB),
Average color, standard deviation, degree of skewness color, color and luster chromatic value, texture contrast, average gray etc., by epithelium
Colour of skin pool and the calculating of colourity, it can be deduced that input the series of parameters arrays such as subject's skin color and luster and the colourity of facial image.
In the present embodiment, texture comparison's angle value is calculated with skin-texture detection algorithm.Texture is the feature of facial image,
And the big feature of texture in itself is the repetition of its pattern.Here, introducing term " texture primitive ", its meaning is what fingerprint was managed
Mode unit, size, shape, color and the orientation of texture primitive can change in very big section, and any two texture
Between difference can be presented as the intensity of variation of texture primitive.A texture co-occurrence matrix can be built, texture co-occurrence matrix C
(i, j) is by displacement vector Dx、DyDefined in=(Δ X, Δ Y), wherein Δ X, Δ Y are respectively on x directions and y directions
Displacement, then calculate all pixels and be separated by displacement Dx、DyPossessed gray level i and j.It is also likely to be due to the line in image
The spatial statisticses distribution of primitive is managed, and includes the important informations such as the structure arrangement on the imaging surface in bottom.Then, it is right
Each element in Matrix C (I, j) is normalized.By being calculated to more than, a series of ginsengs of dermatoglyph can be calculated
Number array, the calculation formula of texture contrast numerical value are：
It can thus be concluded that to input facial image in subject's skin texture to spend than size, also can just represent subject's skin
The weight of texture.
In the present embodiment, using sum of squares of deviations method and the gray value Fast Match Algorithm of the facial image, obtain following
Calculation formula：
Wherein, E (Si,j) with E (T) be user's skin subgraph S respectivelyi,jWith the skin image T (m, n) in presetting database
Average gray.
Then, by extracting numerical value obtained as above, Data Matching is carried out with default skin problem database, it is final to obtain
To the skin problem of matching, and client is back to, as shown in Figure 2.
The technical scheme provided above the embodiment of the present invention is described in detail, specific case used herein
The principle and embodiment of the embodiment of the present invention are set forth, the explanation of above example is only applicable to help and understands this
The principle of inventive embodiments；Meanwhile for those of ordinary skill in the art, according to the embodiment of the present invention, in specific embodiment party
There will be changes in formula and application, in summary, this specification content should not be construed as limiting the invention.
Claims (4)
1. the recognition methods of a kind of skin type and skin problem, it is characterised in that comprise the following steps successively：
S1, use camera device acquisition facial image；
Whether S2, the detection facial image include face, and when it is determined that the facial image includes face, jump procedure
S3；Before the step S3 is performed, photo-irradiation treatment is performed to the facial image, the facial image is utilized into Nogata
Figure regulation is changed, wherein the calculation formula of the conversion is：
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S3, skin colour and colorimetric detection are carried out to the facial image, wherein the calculation formula of the detection is：
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Value；
S6, abovementioned steps S3 to S5 calculating acquired results are matched with pre-set skin issue database, and output matching institute
The skin problem result obtained.
2. recognition methods according to claim 1, it is characterised in that before the recognition methods is implemented, initially set up
Include the skin image storehouse of various typical faces.
3. recognition methods according to claim 1, it is characterised in that the step S2 utilizes network neural method, feature base
Quasi- method or primary standard of color method detect whether the facial image includes face.
4. recognition methods according to claim 1, it is characterised in that turn the facial image using histogram specification
After changing, then 3 × 3 medium filterings are carried out, remove the noise information introduced in image.
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| CN105224808B (en) * | 2015-10-15 | 2018-02-06 | 北京工商大学 | Projecting integral's function skin condition integrated evaluating method based on three-dimensional coordinate |
| CN105787929B (en) * | 2016-02-15 | 2018-11-27 | 天津大学 | Skin rash point extracting method based on spot detection |
| CN106408603B (en) * | 2016-06-21 | 2023-06-02 | 北京小米移动软件有限公司 | Shooting method and device |
| CN106295615A (en) * | 2016-08-23 | 2017-01-04 | 姜汇洋 | Skin detection based on mobile interchange terminal and auxiliary maintenance system |
| CN106875391A (en) * | 2017-03-02 | 2017-06-20 | 深圳可思美科技有限公司 | The recognition methods of skin image and electronic equipment |
| CN106952252B (en) * | 2017-03-06 | 2020-04-21 | 武汉嫦娥医学抗衰机器人股份有限公司 | Skin imaging system based on three spectrums |
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| CN109299632A (en) * | 2017-07-25 | 2019-02-01 | 上海中科顶信医学影像科技有限公司 | Skin detecting method, system, equipment and storage medium |
| CN109671046B (en) * | 2017-10-12 | 2021-08-17 | 精诚工坊电子集成技术（北京）有限公司 | Method and device for analyzing skin moisture by using skin image |
| CN108701217A (en) * | 2017-11-23 | 2018-10-23 | 深圳和而泰智能控制股份有限公司 | A kind of face complexion recognition methods, device and intelligent terminal |
| CN110110637A (en) * | 2019-04-25 | 2019-08-09 | 深圳市华嘉生物智能科技有限公司 | A kind of method of face wrinkle of skin automatic identification and wrinkle severity automatic classification |
| CN110443120A (en) * | 2019-06-25 | 2019-11-12 | 深圳英飞拓科技股份有限公司 | A kind of face identification method and equipment |
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