Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Illumination face recognition method based on completed local convex-and-concave pattern

A face recognition, partial technology, applied in the field of illumination face recognition

Active Publication Date: 2015-09-02
KUNMING UNIV OF SCI & TECH
View PDF6 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a face recognition method based on complete local convex-convex pattern, which is used to solve the face recognition problem in the light environment

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
  • Illumination face recognition method based on completed local convex-and-concave pattern
  • Illumination face recognition method based on completed local convex-and-concave pattern
  • Illumination face recognition method based on completed local convex-and-concave pattern

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] Embodiment 1: as Figure 1-7 As shown, an illuminated face recognition method based on a complete local convex-concave pattern first divides the image into blocks; then performs bilinear interpolation on each block image, so that each pixel in the image can construct 8 symmetrical directions, Then calculate the local difference of each pixel in the block image along 8 directions; then encode the sign feature and amplitude feature of the local difference; encode each pixel of each image block to obtain the central pixel feature of each image block; Next, extract the histogram feature vector from the feature matrix of the symbol feature, amplitude feature, and center pixel feature of each block image, and connect the histogram feature vectors of the block image symbol feature, amplitude feature, and center pixel feature in turn to obtain each block The histogram feature vector of the image; finally, the histogram feature vector of each block image is connected to obtain t...

Embodiment 2

[0055] Embodiment 2: as Figure 1-7 As shown, an illuminated face recognition method based on a complete local convex-concave pattern first divides the image into blocks; then performs bilinear interpolation on each block image, so that each pixel in the image can construct 8 symmetrical directions, Then calculate the local difference of each pixel in the block image along 8 directions; then encode the sign feature and amplitude feature of the local difference; encode each pixel of each image block to obtain the central pixel feature of each image block; Next, extract the histogram feature vector from the feature matrix of the symbol feature, amplitude feature, and center pixel feature of each block image, and connect the histogram feature vectors of the block image symbol feature, amplitude feature, and center pixel feature in turn to obtain each block The histogram feature vector of the image; finally, the histogram feature vector of each block image is connected to obtain t...

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 relates to an illumination face recognition method based on a completed local convex-and-concave pattern, and belongs to the pattern recognition field. The method includes the steps of dividing an image; carrying out bilinear interpolation for each piece of the image; encoding the symbol characteristic and the amplitude characteristic of a local difference of each pixel point in each piece of the image to obtain a symbol characteristic matrix and an amplitude characteristic matrix of each piece of the image; encoding pixel points of each piece of the image to obtain a central pixel characteristic matrix of each piece of the image, extracting the histogram characteristics of the three characteristic matrixes to obtain three characteristic vectors, and successively connecting the three characteristic vectors to obtain histogram characteristic vectors of all pieces of the image; and finally connecting the histogram characteristic vectors of all pieces of the image to obtain a histogram characteristic vector of the original image, sending the characteristic vector to the nearest neighboring classifier to be classified, and verifying the identity of an original face image. The method is an image texture description method based on second-order differential, and is capable of effectively identifying human faces in an illumination environment.

Description

technical field [0001] The invention relates to an illuminated face recognition method based on a complete local convex-concave pattern, which belongs to the technical field of pattern recognition. Background technique [0002] Local binary pattern (LBP) [L.Wang and D.C.He, "Texture classification using texture spectrum", Pattern Recognition, vol.23, pp.905-910, 1990.] is an important image feature The extraction operator has the characteristics of small amount of calculation and effective. Although LBP has achieved great success in the fields of computer vision and pattern recognition, its working mechanism still needs to be improved. Dominant local binary patterns (DLBP) [S.Liao, M.W.K.Law, and A.C.S.Chung, "Dominant local binary patterns for texture classification," IEEE Trans.Image Process., vol.18, no.5 , pp.1107–1118, May 2009.] On the basis of all the LBP modes of the statistical image, the higher frequency modes are screened out, and the high frequency modes with a...

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): G06K9/00
CPCG06V40/162
Inventor 陈熙晋杰
Owner KUNMING UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com