Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A technology of face recognition and face image, which is applied in the field of face recognition, can solve the problems of high feature dimension and single fusion feature, and achieve the effect of overcoming accessories, small amount of data, and improving recognition accuracy
Active Publication Date: 2013-10-16
SHANGHAI LINGZHI TECH CO LTD
View PDF2 Cites 20 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
The features fused by this type of fusion method are generally relatively single, and the feature dimension is relatively high.
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
Embodiment 1
[0047] Such as figure 1 and 2 As shown, the present invention provides a face recognition method, including step S1 to step S11.
[0048] Step S1, collect multi-band training images of visible light, near-infrared, mid-infrared, far-infrared and thermal infrared; specifically, this embodiment proposes the concept of an image group, which means that the face is in the same state, and the obtained visible light , near-infrared, mid-infrared, far-infrared and thermal-infrared face images, such five images are called a set of image groups.
[0049] Step S2, normalize the acquired training images of each band, and pre-process the mask and illumination; specifically, normalize the face images through measures such as human eye positioning, and then cover the mask film to remove the background. At the same time, in order to remove the influence of uneven lighting, lighting preprocessing methods such as Gamma correction or retina filter are added.
[0050] Step S3, extracting the ...
Embodiment 2
[0092] Such as Figure 4 As shown, the present invention also provides another face recognition system, including a first collection module 1, a first processing module 2, a first feature module 3, a first new feature module 4, a second feature set module 5, a second Collection module 6 , second processing module 7 , second feature module 8 , second new feature module 9 , first result module 10 and second result module 11 .
[0093] The first collection module 1 is used to collect multi-band training images of visible light, near-infrared, mid-infrared, far-infrared and thermal infrared;
[0094] The first processing module 2 is configured to normalize the acquired training images of each band, and perform preprocessing of mask and illumination;
[0095] The first feature module 3 is used to extract the first human face image feature of this band from the training image of each band through normalization and preprocessing;
[0096] Preferably, the first face image feature an...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more
PUM
Login to view more
Abstract
The invention provides a method and system for face identification. The method comprises the following steps: collecting multi-band training images of visible, near-infrared, intermediate-infrared, far-infrared, and thermal-infrared lights; carrying out evaluation and selection on extracted face image characteristics of all bands based on a sparse regularization method so as to obtain new characteristics of the face images of all the bands and corresponding new characteristic evaluation indexes after dimensionality reduction; carrying out evaluation, selection and fusion on a first characteristic set based on the parse regularization method so as to construct a second characteristic set finally expressing a face and a corresponding second characteristic evaluation index; obtaining a second characteristic set for finally expressing a face of a to-be-tested person from a third characteristic set according to a second characteristic evaluation index; and employing a nearest neighbor classifier to obtaining a classification result. According to the invention, on the basis of fusion of enough face image information, a characteristic set for finally expressing a face is ensured to have the low dimensionality, thereby ensuring the speed of face identification and the low data volume that an individual needs to store and thus improving identification precision.
Description
technical field [0001] The invention relates to a layered face recognition method for evaluating, selecting and merging multi-band face image features based on a sparse regularization method. Background technique [0002] Face recognition technology uses a computer to obtain face images and perform analysis and preprocessing, then extracts features that can effectively represent face images in a specific way, and finally uses machine learning to identify face images. Face recognition is widely used in human-computer interaction systems, security verification systems, verification of driver's licenses and passports, and identification of criminals. With the development of information and network technology in recent years, face recognition has become one of the most concerned issues in the field of pattern recognition. [0003] One of the most important research topics in the field of face recognition is to find efficient and low-dimensional features or feature sets to descr...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to view more 
Login to view more