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Research on Skeletonization of Palmprint Image

Authors: Yuanfang Liu; Yan Zheng; Guangshun Shi; Qingren Wang;

Research on Skeletonization of Palmprint Image

Abstract

Skeletonization is an important procedure of automated palmprint identification system based on the characteristic of minutiae. Skeleton acquired by traditional thinning algorithms will produce many spurious minutiae which are caused by spurs and misconnections between ridges. The excessive erosion is also a common problem in thinning algorithm. Moreover, unit skeleton cannot be produced by some of these algorithms. In this paper, we introduce a thinning algorithm, which is based on Rotation Invariant Thinning Algorithm introduced by Ahmed and Ward [1] (A-W). The proposed method can solve the above problems. The experimental result shows some skeletons from local regions of palmprint images and running time of the algorithm, which shows that the proposed algorithm can achieve better performance without reducing efficiency.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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