Method for distinguishing false iris images based on robust texture features and machine learning

An iris image and texture feature technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as reduced user cooperation requirements and reduced picture quality, and achieves improved stability, good generalization ability, and improved safety effect

Active Publication Date: 2010-12-22
BEIJING IRISKING
View PDF6 Cites 52 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As the iris recognition system develops in the direction of user-friendliness and ease of use, the requirements for user cooperation are reduced, which will lead to problems such as degradation of picture quality, which makes the authenticity of iris face more challenges.

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
  • Method for distinguishing false iris images based on robust texture features and machine learning
  • Method for distinguishing false iris images based on robust texture features and machine learning
  • Method for distinguishing false iris images based on robust texture features and machine learning

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment

[0072] Specific examples provided by the invention are as follows:

[0073] The present invention is especially suitable for the iris recognition system of suspect screening. For example, the self-service registration system of an airport adopts the iris recognition technology, and the system is connected with the iris database of fugitive criminal suspects of the Public Security Bureau. A criminal suspect, Zhang San, was wanted by the public security organ, and his iris information was put into the fugitive criminal suspect's iris database (blacklist). When Zhang San dressed up in disguise and wore printed contact lenses, and used a fake passport to flee by plane, when using the self-service registration system, the system took an image of Zhang San’s iris, automatically judged that he was wearing printed contact lenses, and started calling the police . Remind the staff to ask Zhang San to remove his glasses and re-identify, focusing on checking Zhang San's identity. Althou...

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 a method for distinguishing false iris images based on robust texture features and machine learning, which comprises the following steps: preprocessing true iris images or false iris images; extracting the partitioned statistical features of a robust weighted partial binary pattern; and carrying out training and sorting of a support vector machine, and judging whether thetest images are false iris images or not according to the output result of a sorter. The method of the invention combines SIFT descriptors and partial binary pattern features to extract the robust texture features, the description of textures is more stable because of the robustness of the SIFT to brightness, translation, rotation and scale change, and the support vector machine enables the method to have better universality. The invention can be used for effectively distinguishing the false iris images, has the advantages of high precision, high robustness and high reliability, can be used for distinguishing false irises such as paper printing irises, color printing contact lenses, synthetic eyes and the like, and can improve the safety of the system when being applied to the applicationsystem in which iris recognition is used for carrying out identification.

Description

technical field [0001] The invention relates to computer vision, digital image processing and pattern recognition, especially a method for discriminating fake iris images based on robust texture features and machine learning. Background technique [0002] At present, identification based on biometrics has been valued by governments of various countries and has penetrated into every aspect of people's daily life. Iris-based biometric identification technology has received more and more attention in the past ten years, and related research and technology have also developed rapidly. It has been successfully used in e-commerce, financial securities, information security, transportation, public security and justice and other occasions. As iris recognition moves from experiment to practicality and has been applied in many security prevention and control fields, the iris recognition system itself is also facing security problems, and various forms of system attacks have emerged. ...

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): G06K9/00G06K9/62
Inventor 谭铁牛孙哲南张慧
Owner BEIJING IRISKING
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