Source:http://linkedlifedata.com/resource/pubmed/id/17281759
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:dateCreated |
2007-2-6
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| pubmed:abstractText |
In this paper, we proposed a novel iris localization algorithm based on the gray distributions of eye images. Firstly, according to the gray features, find a point inside the pupil using a gray value summing operator. Next, starting from this point, find three inner boundary points using a boundary detection template, and then calculate the circle parameters of inner boundary according to the principle that three points which are not on the same line can define a cricle. Finally, find three iris outer boundary points utilizing the similar algorithm and obtain the circle parameters. A large number of experiments on the CASIA iris image database demonstrated that the localization results of proposed algorithm are more accurate and more rapid than any other classical algorithms, such as Daugman's algorithm and Hough transform.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
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| pubmed:issn |
1557-170X
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
6
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
6504-7
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| pubmed:year |
2005
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| pubmed:articleTitle |
A novel iris localization algorithm based on the gray distributions of eye images.
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| pubmed:affiliation |
Computer Vision Group, Shenyang University of Technology, Box 29, No.1, South Thirteenth Road, Tiexi District, Shenyang 110023, China. yuan60@126.com.
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| pubmed:publicationType |
Journal Article
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