NDLI: Fingerprint pre-segmentation method based on Mean Shift Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Liu Xinmei Hou Wen Yin Junling Han Yan
Copyright Year	2011
Description	Author affiliation: School of Information and Communication Engineering, North University of China, Taiyuan, China (Hou Wen; Han Yan) \|\| National Key Lab of Electronic Test Technology, North University of China, Taiyuan, China (Liu Xinmei) \|\| Department of Electronic and Mechanical Industry of Shanxi Province, Taiyuan, China (Yin Junling)
Abstract	In the research or application of fingerprint images, people focus on the region where the ridges are seen. The background region of the whole image contains various degrees of noise caused by unevenly pressing of the fingerprint and the contaminated camera lens. This phenomenon calls for the considerations of noise elimination, image enhancement, and pre-segmentation. Mean Shift algorithm is a nonparametric statistics method that searches for the most approximate mode to the sample distribution. The fingerprint pre-segmentation method based on mean shift algorithm was studied and applied in a number of images stored in FVC2004 image Database. The results show that the Mean Shift method is applicable to most images. There are very few results are out of the optimal ones.
Starting Page	1241
Ending Page	1245
File Size	831931
Page Count	5
File Format	PDF
ISBN	9781424493043
e-ISBN	9781424493067
DOI	10.1109/CISP.2011.6100446
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image matching Mean Shift Noise Estimation Fingerprint Segmentation Fingerprint recognition Vectors kernel function Kernel
Content Type	Text
Resource Type	Article

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