CN104021397A - Face identifying and comparing method and device - Google Patents
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- CN104021397A CN104021397A CN201410263029.9A CN201410263029A CN104021397A CN 104021397 A CN104021397 A CN 104021397A CN 201410263029 A CN201410263029 A CN 201410263029A CN 104021397 A CN104021397 A CN 104021397A
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Abstract
The invention provides a face identifying and comparing method and device. The face identifying and comparing method comprises the steps that firstly, an image of a picture of a detected person is obtained; secondly, an image of an identification card of the detected person is obtained; thirdly, face detection is conducted on the image of the picture and the image of the identification card respectively, and then a picture face image and an identification card face image are obtained; fourthly, the picture face image and the identification card face image are preprocessed so that the comparison effect can be improved; fifthly, feature extraction is conducted on the preprocessed picture face image and the preprocessed identification card face image; sixthly, extracted picture face image features and extracted identification card face image features are trained, so that a picture face image feature vector and an identification card face image feature vector are obtained; seventhly, the picture face image feature vector and the identification card face image feature vector are compared. By the adoption of the face identifying and comparing method and device, comparison between the picture image and the identification card image of the detected person can be compared, and an accurate comparison result can be obtained.
Description
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Technical field
The present invention relates to face recognition technology, relate in particular to a kind of recognition of face comparison method and device.
Background technology
In recent years, along with advancing by leaps and bounds of social development and science and technology, the high speed development of computer vision technique and mode identification technology, face recognition technology has become a heat subject in vision and identification field.Face recognition technology is the recognition method based on biological characteristic, is one of the most outstanding ability of human vision, and its research relates to a lot of fields, as image processing, pattern-recognition, artificial intelligence etc.Compare with features such as fingerprint recognition, iris recognition, voice recognitions, recognition of face has conveniently, directly, friendly, initiatively, the advantage such as nature, under the prerequisite of not disturbing measured, can obtain its face-image simultaneously, for measured without any mental handicape, and whole system is without specific collecting device, cost is also lower, makes face recognition technology obtain gradually people's acceptance.The research institution of a lot of countries is engaged in school and commercial company the research that recognition of face is relevant at present, and has had development faster in 20 end of the centurys.Yet, along with development in science and technology, the requirement of the convenience of recognition of face and accuracy all constantly being increased, existing face recognition technology is difficult to meet demand for development.
Summary of the invention
In view of this, the invention provides a kind of recognition of face comparison method and device, can compare to detected person's photograph image and ID Card Image, accurately obtain comparison result.
A kind of recognition of face comparison method provided by the invention, comprising:
Step 1: the photograph image that obtains detected person;
Step 2: the ID Card Image that obtains detected person;
Step 3: respectively described photograph image and ID Card Image are carried out to the detection of people's face, obtain photo facial image and I.D. facial image;
Step 4: comparison film facial image and I.D. facial image carry out pre-service to strengthen comparison effect respectively;
Step 5: respectively pretreated photo facial image and I.D. facial image are carried out to feature extraction;
Step 6: extracted photo facial image feature and I.D. facial image feature are carried out to features training and obtain photo facial image proper vector and I.D. facial image proper vector;
Step 7: comparison film facial image proper vector and I.D. facial image proper vector are compared, obtains matching result.
Described step 1 adopts CCD camera to obtain detected person's photograph image.
Described step 2 adopts card reader of ID card to obtain detected person's ID Card Image.
Described step 3 comprises:
Step 3.1: determine in the entire image obtaining whether have people's face;
Step 3.2: if there is people's face, determine the position of people's face in entire image;
Step 3.3: the position according to people's face in entire image, entire image is divided as people face part and non-face part;
Step 3.4: the people face part in extraction entire image is as facial image.
Described step 3 also comprises, step 3.5: by I.D. facial image scaled be square.
The pre-service of described step 4 comprises carries out illumination compensation, gray balance, level and smooth noise reduction, Local Features Analysis and normalized to image.
Described step 5 comprises:
Step 5.1: generate Gabor kernel function according to setting dimensional parameters and direction parameter;
Step 5.2: form Gabor wave filter according to Gabor kernel function;
Step 5.3: utilize Gabor window to sample pretreated facial image;
Step 5.4: the facial image after utilizing Gabor wave filter to sampling carries out filtering transformation and obtains Gabor feature;
Step 5.5: Gabor feature is chosen and obtained facial image feature.
Described step 7 comprises:
Step 7.1: utilize described photo facial image proper vector and I.D. facial image proper vector, set up a plurality of Markov models, calculate the likelihood value that each Markov model is corresponding;
Step 7.2: choose maximum likelihood value as matching result from a plurality of likelihood values that calculate.
In addition, the present invention also provides a kind of recognition of face comparison device, comprising:
Photograph image acquisition module: for obtaining detected person's photograph image;
ID Card Image acquisition module: for obtaining detected person's ID Card Image;
People's face detection module: for described photograph image and ID Card Image are carried out to the detection of people's face, obtain photo facial image and I.D. facial image;
Pretreatment module: carry out pre-service to strengthen comparison effect for comparison film facial image and I.D. facial image;
Characteristic extracting module: for pretreated photo facial image and I.D. facial image are carried out to feature extraction;
Features training module: carry out features training for the photo facial image feature to extracted and I.D. facial image feature and obtain photo facial image proper vector and I.D. facial image proper vector;
Comparing module: compare for comparison film facial image proper vector and I.D. facial image proper vector, obtain matching result.
Described photograph image acquisition module is CCD camera.
Described ID Card Image acquisition module is card reader of ID card.
Described people's face detection module comprises that determination module, locating module, image cut apart module, image extraction module, wherein,
Determination module: for determining whether the entire image obtaining exists people's face;
Locating module: for determining that people's face is in the position of entire image;
Image is cut apart module: for the position in entire image according to people's face, entire image is divided as people face part and non-face part;
Image extraction module: for the people face part of extracting entire image as facial image.
Described people's face detection module also comprises that image dwindles module, for by I.D. facial image scaled be square.
Pretreatment module is for carrying out illumination compensation, gray balance, level and smooth noise reduction, Local Features Analysis and normalized to image.
Characteristic extracting module comprises that Gabor kernel function generation module, Gabor wave filter build module, sampling module, filtration module, characteristic selecting module, wherein,
Gabor kernel function generation module: for generating Gabor kernel function according to setting dimensional parameters and direction parameter;
Gabor wave filter builds module: for forming Gabor wave filter according to Gabor kernel function;
Sampling module: for utilizing Gabor window to sample pretreated facial image;
Filtration module: carry out filtering transformation for the facial image after utilizing Gabor wave filter to sampling and obtain Gabor feature;
Characteristic selecting module: for Gabor feature is chosen and obtained facial image feature.
Described comparing module comprises likelihood value computing module and matching result output module, wherein,
Described likelihood value computing module, for utilizing described photo facial image proper vector and I.D. facial image proper vector, sets up a plurality of Markov models, calculates the likelihood value that each Markov model is corresponding;
Described matching result output module, chooses maximum likelihood value for a plurality of likelihood values that obtain from described likelihood value computing module and exports as matching result.
In sum, the advantage of recognition of face comparison method of the present invention and device comprises:
Easy to use: the present invention uses general video camera as identifying information acquisition device, be a kind of mode of Entirely contactless, in the situation that not discovering, identifying object completes identifying, and can there is not psychological repellence mood in identifying object.
Intuitive is outstanding: people's face is undoubtedly the information source the most intuitively that naked eyes can be differentiated, and face recognition technology is used according to people's face-image just, facilitates manual confirmation, audit, and " judging people solely by appearance " meets people's cognitive law.
Be difficult for counterfeit: the present invention requires identifying object must come to identification scene personally, other people are difficult to counterfeit, the unique active discriminating power of face recognition technology has guaranteed that other people cannot cheat recognition system with inactive photo, puppet, waxen imagen, and this is that the biometrics identification technologies such as fingerprint are difficult to accomplish.
Identification accuracy is high, and speed is fast: compare with other biological identification technology, the accuracy of identification of face recognition technology is in higher level, and misclassification rate, to refuse to recognize rate lower.
Use versatility equipment: equipment used in the present invention is generally the common apparatus such as PC, video camera; because computing machine, closed-circuit TV monitoring system etc. have been widely applied at present; therefore; for most users; use face recognition technology without adding a large amount of specialized equipments; not only protect user's original investment but also greatly expanded systemic-function, also improved the security performance of system simultaneously, met user's security requirement.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or scheme of the prior art, to the accompanying drawing of required use in embodiment be briefly described below, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
The schematic flow sheet of the recognition of face comparison method that Fig. 1 provides for one embodiment of the invention;
The structural representation of the recognition of face comparison device that Fig. 2 provides for one embodiment of the invention.
Embodiment
For making object, technical scheme and the advantage of the embodiment of the present invention clearer, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is carried out to clear, complete description, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Embodiment based in the present invention, the every other embodiment that those of ordinary skills obtain under the prerequisite of not making creative work, belongs to the scope of protection of the invention.
The schematic flow sheet of the recognition of face comparison method that Fig. 1 provides for one embodiment of the invention, as shown in Figure 1, the recognition of face comparison method of the present embodiment can comprise:
Step 1: the photograph image that obtains detected person; Can adopt CCD camera to obtain detected person's photograph image.
Step 2: the ID Card Image that obtains detected person; Can adopt card reader of ID card to obtain detected person's ID Card Image.
Step 3: respectively described photograph image and ID Card Image are carried out to the detection of people's face, obtain photo facial image and I.D. facial image;
Alternatively, described step 3 comprises:
Step 3.1: determine in the entire image obtaining whether have people's face;
Step 3.2: if there is people's face, determine the position of people's face in entire image;
Step 3.3: the position according to people's face in entire image, entire image is divided as people face part and non-face part;
Step 3.4: the people face part in extraction entire image is as facial image.
Alternatively, described step 3 also comprises, step 3.5: by I.D. facial image scaled be square.The picture quality gathering due to I.D. is not high, and in identifying, the factors such as background, collar, light have impact to a certain degree to discrimination.In order to reduce the impact of various factors on discrimination, in systematic realizing program, we dwindle into square by people's face frame ratio of I.D. image detect, like this, reduce the impact of other factors on face characteristic information on the one hand, improved on the other hand face characteristic and extracted and matching speed.
Step 4: comparison film facial image and I.D. facial image carry out pre-service to strengthen comparison effect respectively;
Alternatively, the pre-service of described step 4 comprises image is carried out to illumination compensation, gray balance, level and smooth noise reduction, Local Features Analysis and normalized.
Step 5: respectively pretreated photo facial image and I.D. facial image are carried out to feature extraction;
Alternatively, described step 5 comprises:
Step 5.1: generate Gabor kernel function according to setting dimensional parameters and direction parameter;
Step 5.2: form Gabor wave filter according to Gabor kernel function;
Step 5.3: utilize Gabor window to sample pretreated facial image;
Step 5.4: the facial image after utilizing Gabor wave filter to sampling carries out filtering transformation and obtains Gabor feature;
Step 5.5: Gabor feature is chosen and obtained facial image feature.
Step 6: extracted photo facial image feature and I.D. facial image feature are carried out to features training and obtain photo facial image proper vector and I.D. facial image proper vector;
Step 7: comparison film facial image proper vector and I.D. facial image proper vector are compared, obtains matching result.
Alternatively, described step 7 comprises:
Step 7.1: the observation sequence vector that obtains facial image to be identified;
Step 7.2: the likelihood value that calculates the described observation sequence vector of N model generation;
Step 7.3: obtain the model of the likelihood value maximum that makes described observation sequence vector as the model of coupling facial image to be identified.
The structural representation of the recognition of face comparison device that Fig. 2 provides for one embodiment of the invention, as shown in Figure 2, the recognition of face comparison device of the present embodiment, can comprise:
Photograph image acquisition module: for obtaining detected person's photograph image; Alternatively, described photograph image acquisition module is CCD camera.
ID Card Image acquisition module: for obtaining detected person's ID Card Image; Alternatively, described ID Card Image acquisition module is card reader of ID card.
People's face detection module: for described photograph image and ID Card Image are carried out to the detection of people's face, obtain photo facial image and I.D. facial image;
Alternatively, described people's face detection module comprises that determination module, locating module, image cut apart module, image extraction module, wherein,
Determination module: for determining whether the entire image obtaining exists people's face;
Locating module: for determining that people's face is in the position of entire image;
Image is cut apart module: for the position in entire image according to people's face, entire image is divided as people face part and non-face part;
Image extraction module: for the people face part of extracting entire image as facial image.
Pretreatment module: carry out pre-service to strengthen comparison effect for comparison film facial image and I.D. facial image; Alternatively, described pretreatment module can be carried out illumination compensation, gray balance, level and smooth noise reduction, Local Features Analysis and normalized to image.
Characteristic extracting module: for pretreated photo facial image and I.D. facial image are carried out to feature extraction;
Alternatively, characteristic extracting module comprises that Gabor kernel function generation module, Gabor wave filter build module, sampling module, filtration module, characteristic selecting module, wherein,
Gabor kernel function generation module: for generating Gabor kernel function according to setting dimensional parameters and direction parameter;
Gabor wave filter builds module: for forming Gabor wave filter according to Gabor kernel function;
Sampling module: for utilizing Gabor window to sample pretreated facial image;
Filtration module: carry out filtering transformation for the facial image after utilizing Gabor wave filter to sampling and obtain Gabor feature;
Characteristic selecting module: for Gabor feature is chosen and obtained facial image feature.
Features training module: carry out features training for the photo facial image feature to extracted and I.D. facial image feature and obtain photo facial image proper vector and I.D. facial image proper vector;
Comparing module: compare for comparison film facial image proper vector and I.D. facial image proper vector, obtain matching result.
In sum, the advantage of recognition of face comparison method of the present invention and device comprises:
Easy to use: the present invention uses general video camera as identifying information acquisition device, be a kind of mode of Entirely contactless, in the situation that not discovering, identifying object completes identifying, and can there is not psychological repellence mood in identifying object.
Intuitive is outstanding: people's face is undoubtedly the information source the most intuitively that naked eyes can be differentiated, and face recognition technology is used according to people's face-image just, facilitates manual confirmation, audit, and " judging people solely by appearance " meets people's cognitive law.
Be difficult for counterfeit: the present invention requires identifying object must come to identification scene personally, other people are difficult to counterfeit, the unique active discriminating power of face recognition technology has guaranteed that other people cannot cheat recognition system with inactive photo, puppet, waxen imagen, and this is that the biometrics identification technologies such as fingerprint are difficult to accomplish.
Identification accuracy is high, and speed is fast: compare with other biological identification technology, the accuracy of identification of face recognition technology is in higher level, and misclassification rate, to refuse to recognize rate lower.
Use versatility equipment: equipment used in the present invention is generally the common apparatus such as PC, video camera; because computing machine, closed-circuit TV monitoring system etc. have been widely applied at present; therefore; for most users; use face recognition technology without adding a large amount of specialized equipments; not only protect user's original investment but also greatly expanded systemic-function, also improved the security performance of system simultaneously, met user's security requirement.
Finally it should be noted that: above embodiment only, in order to technical scheme of the present invention to be described, is not intended to limit; Although the present invention is had been described in detail with reference to previous embodiment, those of ordinary skill in the art is to be understood that: its technical scheme that still can record aforementioned each embodiment is modified, or part technical characterictic is wherein equal to replacement, and these modifications or replacement do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (16)
1. a recognition of face comparison method, is characterized in that, described method comprises:
Step 1: the photograph image that obtains detected person;
Step 2: the ID Card Image that obtains detected person;
Step 3: respectively described photograph image and ID Card Image are carried out to the detection of people's face, obtain photo facial image and I.D. facial image;
Step 4: comparison film facial image and I.D. facial image carry out pre-service to strengthen comparison effect respectively;
Step 5: respectively pretreated photo facial image and I.D. facial image are carried out to feature extraction;
Step 6: extracted photo facial image feature and I.D. facial image feature are carried out to features training and obtain photo facial image proper vector and I.D. facial image proper vector;
Step 7: comparison film facial image proper vector and I.D. facial image proper vector are compared, obtains matching result.
2. a kind of recognition of face comparison method according to claim 1, is characterized in that, described step 1 adopts CCD camera to obtain detected person's photograph image.
3. a kind of recognition of face comparison method according to claim 1, is characterized in that, described step 2 adopts card reader of ID card to obtain detected person's ID Card Image.
4. a kind of recognition of face comparison method according to claim 1, is characterized in that, described step 3 comprises:
Step 3.1: determine in the entire image obtaining whether have people's face;
Step 3.2: if there is people's face, determine the position of people's face in entire image;
Step 3.3: the position according to people's face in entire image, entire image is divided as people face part and non-face part;
Step 3.4: the people face part in extraction entire image is as facial image.
5. a kind of recognition of face comparison method according to claim 4, is characterized in that, described step 3 also comprises, step 3.5: by I.D. facial image scaled be square.
6. a kind of recognition of face comparison method according to claim 1, is characterized in that, the pre-service of described step 4 comprises carries out illumination compensation, gray balance, level and smooth noise reduction, Local Features Analysis and normalized to image.
7. a kind of recognition of face comparison method according to claim 1, is characterized in that, described step 5 comprises:
Step 5.1: generate Gabor kernel function according to setting dimensional parameters and direction parameter;
Step 5.2: form Gabor wave filter according to Gabor kernel function;
Step 5.3: utilize Gabor window to sample pretreated facial image;
Step 5.4: the facial image after utilizing Gabor wave filter to sampling carries out filtering transformation and obtains Gabor feature;
Step 5.5: Gabor feature is chosen and obtained facial image feature.
8. a kind of recognition of face comparison method according to claim 1, is characterized in that, described step 7 comprises:
Step 7.1: utilize described photo facial image proper vector and I.D. facial image proper vector, set up a plurality of Markov models, calculate the likelihood value that each Markov model is corresponding;
Step 7.2: choose maximum likelihood value as matching result from a plurality of likelihood values that calculate.
9. a recognition of face comparison device, is characterized in that, described device comprises:
Photograph image acquisition module: for obtaining detected person's photograph image;
ID Card Image acquisition module: for obtaining detected person's ID Card Image;
People's face detection module: for described photograph image and ID Card Image are carried out to the detection of people's face, obtain photo facial image and I.D. facial image;
Pretreatment module: carry out pre-service to strengthen comparison effect for comparison film facial image and I.D. facial image;
Characteristic extracting module: for pretreated photo facial image and I.D. facial image are carried out to feature extraction;
Features training module: carry out features training for the photo facial image feature to extracted and I.D. facial image feature and obtain photo facial image proper vector and I.D. facial image proper vector;
Comparing module: compare for comparison film facial image proper vector and I.D. facial image proper vector, obtain matching result.
10. a kind of recognition of face comparison device according to claim 9, is characterized in that, described photograph image acquisition module is CCD camera.
11. a kind of recognition of face comparison devices according to claim 9, is characterized in that, described ID Card Image acquisition module is card reader of ID card.
12. a kind of recognition of face comparison devices according to claim 9, is characterized in that, described people's face detection module comprises that determination module, locating module, image cut apart module, image extraction module, wherein,
Determination module: for determining whether the entire image obtaining exists people's face;
Locating module: for determining that people's face is in the position of entire image;
Image is cut apart module: for the position in entire image according to people's face, entire image is divided as people face part and non-face part;
Image extraction module: for the people face part of extracting entire image as facial image.
13. a kind of recognition of face comparison devices according to claim 12, is characterized in that, described people's face detection module also comprises that image dwindles module, for by I.D. facial image scaled be square.
14. a kind of recognition of face comparison devices according to claim 9, is characterized in that, pretreatment module is for carrying out illumination compensation, gray balance, level and smooth noise reduction, Local Features Analysis and normalized to image.
15. a kind of recognition of face comparison devices according to claim 9, is characterized in that, characteristic extracting module comprises that Gabor kernel function generation module, Gabor wave filter build module, sampling module, filtration module, characteristic selecting module, wherein,
Gabor kernel function generation module: for generating Gabor kernel function according to setting dimensional parameters and direction parameter;
Gabor wave filter builds module: for forming Gabor wave filter according to Gabor kernel function;
Sampling module: for utilizing Gabor window to sample pretreated facial image;
Filtration module: carry out filtering transformation for the facial image after utilizing Gabor wave filter to sampling and obtain Gabor feature;
Characteristic selecting module: for Gabor feature is chosen and obtained facial image feature.
16. a kind of recognition of face comparison methods according to claim 9, is characterized in that, described comparing module comprises likelihood value computing module and matching result output module, wherein,
Described likelihood value computing module, for utilizing described photo facial image proper vector and I.D. facial image proper vector, sets up a plurality of Markov models, calculates the likelihood value that each Markov model is corresponding;
Described matching result output module, chooses maximum likelihood value for a plurality of likelihood values that obtain from described likelihood value computing module and exports as matching result.
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| CN108875646B (en) * | 2018-06-22 | 2022-09-27 | 青岛民航凯亚系统集成有限公司 | Method and system for double comparison and authentication of real face image and identity card registration |
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| CN110370996A (en) * | 2019-07-15 | 2019-10-25 | 浙江宏立至信汽车部件制造有限公司 | Intelligent automobile electric chair |
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