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Fingerprint Image Quality Analysis for Knowledge-based Image Enhancement  

윤은경 (연세대학교 컴퓨터과학과 생체인식연구센터)
조성배 (연세대학교 컴퓨터과학과 생체인식연구센터)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.7, 2004 , pp. 911-921 More about this Journal
Abstract
Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.
Keywords
Biometrics; Fingerprint identification; Fingerprint image quality; Knowledge-based preprocessing; Clustering;
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