Human face recognition method based on image reconstruction and Hash algorithm

A hash algorithm and image reconstruction technology, applied in the field of face recognition, can solve problems such as increasing the time of recognition, ignoring the correlation of face images, and reducing the recognition rate

Active Publication Date: 2015-03-25
上海华美电梯装饰有限公司
View PDF3 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although these algorithms can achieve better recognition results under certain circumstances, there are still some defects: SRC is mainly for single-input face recognition algorithms, and the face images taken by the same individual under different conditions can only be one One determines the identity of the individual through th...

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
  • Human face recognition method based on image reconstruction and Hash algorithm
  • Human face recognition method based on image reconstruction and Hash algorithm
  • Human face recognition method based on image reconstruction and Hash algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0042] First, choose a face database, such as the Yele B database. Yele B contains 38 subjects, and each subject contains 62 to 64 images, with different lighting between images. In this embodiment, each individual selects 5 to 10 pictures as multi-input test pictures, and the rest as training pictures. For each subject, the subject’s test images are composed into a corresponding test matrix X=[x 1 ,...,x k ], 1≤i≤k; the other images in each subject are used as the training images of the subject, the training images of all subjects are integrated into the training data matrix D, and the corresponding labels are generated for the training images of each subject.

[0043] Such as figure 1 The schematic diagram of the training picture and the test picture in the Yale database is shown. The picture on the upper layer represents the training...

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 human face recognition method based on image reconstruction and a Hash algorithm. An image reconstruction model is adopted, a dimension variable ap is used, shields and covers in a human face image are effectively eliminated, and the problems of uneven illumination and image drifting in the human face image are resolved. A Hash matrix is introduced, a high-dimensional data matrix is mapped into a low-dimensional data space, and the calculation amount of the algorithm is largely reduced. Under the condition of guaranteeing recognition accuracy, the problem of multiple inputs in the human face recognition process is effectively resolved, and the recognition efficiency of the algorithm is improved.

Description

technical field [0001] The invention belongs to the technical field of face recognition, in particular to a face recognition method based on image reconstruction and hash algorithm. Background technique [0002] Face recognition is a popular research topic in the field of computer vision. It integrates computer image processing technology and biostatistics principles, uses computer image processing technology to extract portrait feature points from videos, and uses biostatistics principles to analyze and establish Mathematical models have broad prospects for development. For a robust face recognition algorithm, it is necessary to effectively deal with various challenges in face recognition such as face occlusion, camouflage, illumination changes, and image drift. [0003] Recently, the face recognition algorithm (SRC) based on sparse representation proposed by John Wright has attracted more and more attention from researchers. Under the constraints of sparse conditions, SR...

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
CPCG06V40/16
Inventor 胡昭华赵孝磊邢卫国徐玉伟欧阳雯
Owner 上海华美电梯装饰有限公司
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