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http://dx.doi.org/10.3745/KTSDE.2014.3.11.495

Contactless Palmprint Recognition Based on the KLT Feature Points  

Kim, Min-Ki (경상대학교 컴퓨터과학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.3, no.11, 2014 , pp. 495-502 More about this Journal
Abstract
An effective solution to the variation on scale and rotation is required to recognize contactless palmprint. In this study, we firstly minimize the variation by extracting a region of interest(ROI) according to the size and orientation of hand and normalizing the ROI. This paper proposes a contactless palmprint recognition method based on KLT(Kanade-Lukas-Tomasi) feature points. To detect corresponding feature points, texture in local regions around KLT feature points are compared. Then, we recognize palmprint by measuring the similarity among displacement vectors which represent the size and direction of displacement of each pair of corresponding feature points. An experimental results using CASIA public database show that the proposed method is effective in contactless palmprint recognition. Especially, we can get the performance of exceeding 99% correct identification rate using multiple Gabor filters.
Keywords
Contactless Palmprint Recognition; KLT Feature Point; Gabor Filters;
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Times Cited By KSCI : 1  (Citation Analysis)
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