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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15765

Title: Fingerprint Verification using Statistical Descriptors
Authors: Muhammad Khurram Khan
Keywords: Fingerprint
Issue Date: 2010
Publisher: Journal of Digital Signal Processing
Abstract: The importance of high precision matching in fingerprint cannot be over-emphasized. This paper presents a novel fingerprint verification algorithm which improves matching accuracy by overcoming the shortcomings of poor image quality. The proposed method involves determination of a singular point using orientation field reliability, extraction of a square-sub-image (SSI); 129x129 pixels, statistical analysis of the co-occurrence matrices as well as application of dual analyses on experimental results; Pattern Recognition and Image Processing Laboratory (FVC2002) testing protocol and Program for Rate Estimation and Statistical Summaries (PRESS). The efficiency of the proposed method has been demonstrated by the experimental results which show equal error rate (EER) of 28% and a comparatively more accurate and robust means for reliable fingerprint verification.
URI: http://hdl.handle.net/123456789/15765
Appears in Collections:College of Computer and Information Sciences

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