Name
Abstract | ||
|---|---|---|
Iris feature extraction is a key issue in iris recognition. This paper proposes a novel iris feature extraction method based on local binary pattern (LBP) images and the chunked encoding method. Firstly it applies the LBP to the normalized iris image and obtains the iris' LBP image, then extracts the iris's feature via the chunked encoding method based on the iris' statistical information. Finally it completes the iris recognition and classification using Hamming distance. Experimental results showed that this algorithm can get higher recognition rate than the traditional iris feature extraction method, which demonstrated the efficiency of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICNC.2011.6022302 | ICNC |
Keywords | Field | DocType |
chunked encoding,statistical analysis,local binary pattern,iris feature extraction method,hamming distance,iris recognition,lbp encoding,biometrics (access control),feature extraction,biometrics,statistical information,encoding,gray scale,iris | Computer vision,Iris recognition,Normalization (statistics),Pattern recognition,Computer science,Local binary patterns,Feature extraction,Hamming distance,Artificial intelligence,Biometrics,Grayscale,Encoding (memory) | Conference |
Volume | Issue | ISSN |
3 | null | 2157-9555 |
ISBN | Citations | PageRank |
978-1-4244-9950-2 | 4 | 0.69 |
References | Authors | |
11 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuqing He | 1 | 63 | 19.58 |
| Guangqin Feng | 2 | 4 | 0.69 |
| Yushi Hou | 3 | 5 | 1.03 |
| Li Li | 4 | 243 | 64.97 |
| Evangelia Micheli-Tzanakou | 5 | 14 | 4.50 |