LBP (Local Binary Pattern) image and block encoding-based iris feature extracting method

A block coding and feature extraction technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of slow matching speed and large storage space, so as to avoid slow matching, reduce storage space, and improve recognition speed Effect

Inactive Publication Date: 2012-07-04
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF2 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, direct matching based on iris LBP feature images requires large storage space and slow matching speed.

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
  • LBP (Local Binary Pattern) image and block encoding-based iris feature extracting method
  • LBP (Local Binary Pattern) image and block encoding-based iris feature extracting method
  • LBP (Local Binary Pattern) image and block encoding-based iris feature extracting method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] Various details involved in the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0033] In general, the basic components of an iris recognition system are: image acquisition, image preprocessing, feature extraction, and classification decisions. The iris recognition system completes the authentication or identification of the user's identity by extracting the texture features in the test iris image and matching the features with the user's pre-stored feature templates. Therefore, its recognition accuracy is highly dependent on the iris features used, and its recognition speed directly depends on the matching speed of feature templates. It can be seen that feature extraction is a key link in the iris recognition algorithm.

[0034] The iris feature extraction method based on LBP image and block coding that the present invention proposes, its flow chart is as follows figure 1 shown, including ...

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 an LBP (Local Binary Pattern) image and block encoding-based iris feature extracting method comprising the following steps of: firstly, adopting an LBP operator for a normalized iris image to obtain an LBP iris image; then, extracting an iris feature from the LBP image by using an iris statistical information based block encoding method; and finally, taking a Hamming distance as a classifier to obtain a recognition result. Parameters of the LBP operator and block encoding in the feature extracting method are obtained through training. Compared with the traditional feature extracting method, the LBP image and block encoding-based iris feature extracting method has higher recognition rate and strong robustness for illumination change.

Description

technical field [0001] The invention belongs to the field of biological feature recognition, and relates to technologies such as digital image processing, statistical learning and pattern recognition, in particular to an iris feature extraction method based on LBP image and block coding. Background technique [0002] Biometrics is an effective method of personal identification. The human body has many inherent physical and behavioral characteristics that can be used, such as face, fingerprint, iris, vein, voice, etc. Due to the advantages of uniqueness, stability and non-invasiveness, iris recognition is currently the most reliable method, with higher recognition rate and lower equal error rate. Today, iris recognition has become the research focus of biometric technology, and feature extraction is a key issue in iris recognition algorithms. [0003] The earliest automatic iris recognition system was developed by Daugman, who used 2D Gabor filter to perform a simple coarse...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 何玉青冯光琴李力刘勇
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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