CASIA OpenIR  > 智能感知与计算研究中心
Efficient iris recognition by characterizing key local variations
Ma, L; Tan, TN; Wang, YH; Zhang, DX
AbstractUnlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2 255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.
KeywordBiometrics Iris Recognition Local Sharp Variations Personal Identification Transient Signal Analysis Wavelet Transform
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000221466400001
Citation statistics
Document Type期刊论文
AffiliationChinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Ma, L,Tan, TN,Wang, YH,et al. Efficient iris recognition by characterizing key local variations[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2004,13(6):739-750.
APA Ma, L,Tan, TN,Wang, YH,&Zhang, DX.(2004).Efficient iris recognition by characterizing key local variations.IEEE TRANSACTIONS ON IMAGE PROCESSING,13(6),739-750.
MLA Ma, L,et al."Efficient iris recognition by characterizing key local variations".IEEE TRANSACTIONS ON IMAGE PROCESSING 13.6(2004):739-750.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ma, L]'s Articles
[Tan, TN]'s Articles
[Wang, YH]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ma, L]'s Articles
[Tan, TN]'s Articles
[Wang, YH]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ma, L]'s Articles
[Tan, TN]'s Articles
[Wang, YH]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.