Two-dimension linearity discrimination analysis face identification method

A linear identification analysis and face recognition technology, applied in the field of biological pattern recognition, to achieve high recognition rate, high efficiency, and improved separability.

Active Publication Date: 2016-06-01
深圳市兆能讯通科技有限公司
View PDF3 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problems existing in the existing linear discrimination analysis method, and propose a face recognition method of two-dimensional linear discrimination an

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
  • Two-dimension linearity discrimination analysis face identification method
  • Two-dimension linearity discrimination analysis face identification method
  • Two-dimension linearity discrimination analysis face identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0014] The present invention first calculates the intra-class and inter-class scatter matrices, then calculates the product matrix of the inverse of the intra-class scatter matrix and the inter-class scatter matrix, then calculates the eigenvalues ​​and eigenvectors of the product matrix, and calculates the projection matrix, and finally use the projection matrix to project the two-dimensional face image into the projection space, and calculate the recognition rate through the nearest neighbor classifier. details as follows:

[0015] see figure 1 , using the ORL face database as the database. The ORL face database was created by the AT&T laboratory of the University of Cambridge in the United Kingdom. The database contains 400 facial images of 40 people, 10 for each person, and 10 images contain people in different postures, different lighting, different expressions or facial expressions. For the face state under the accessory state, each face image sample matrix is ​​112×92...

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

No PUM Login to view more

Abstract

The invention discloses a two-dimension linearity discrimination analysis face identification method, comprising steps of calculating an affine matrix element according to a chosen training sample matrix, calculating an intra-class divergence matrix and an extra-class divergence matrix according to the affine matrix element, calculating the characteristic value and the characteristic vector of a matrix of the product between the inverse of the intra-class divergence matrix and the extra-class divergence matrix according to the intra-class divergence matrix and the extra-class divergence matrix, solving a projection matrix, using the projection matrix to project the training sample matrix to the projection space to obtain the projected matrix, adopting a neighbor classifier to perform classification processing on the projected matrix and the test sample, and calculating the recognition rate. The invention fuses the advantages of two-dimension linearity discrimination analysis and the two-dimension local projection maintaining method, which not only performs effective dimension reduction on the original data, but also maintain the local characteristics of the data. Furthermore, the invention avoids the fact that the two-dimension structure of the sample data is damaged when the sample data is stretched into one-dimension data, and has high recognition rate and high efficiency.

Description

technical field [0001] The invention relates to the field of biological pattern recognition, in particular to a face recognition technology. Background technique [0002] With the development of computer science and biomedical technology, the use of human biometrics for identification has become an important way. As an important part of biometric technology, face recognition technology has become the most commonly used means of identification in people's daily life. It not only has the universality, security, uniqueness, stability and collectability At the same time, it has the advantages of no need for target cooperation, long-distance execution and intuitive comparison. Therefore, face recognition technology has been widely used in information security, criminal investigation, entrance and exit monitoring and other fields. [0003] Existing face recognition methods include: Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Kernel-based Feature Extra...

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
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/161G06F18/24147
Inventor 武小红杜辉王雪武斌孙俊傅海军
Owner 深圳市兆能讯通科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap