Please use this identifier to cite or link to this item:
|Title:||Ridge directional singular points for fingerprint recognition and matching||Authors:||Dagher, Issam
|Affiliations:||Department of Computer Engineering||Keywords:||Fingerprint
Core and delta
|Issue Date:||2006||Part of:||Applied stochastic models in business and industry||Volume:||22||Issue:||1||Start page:||73||End page:||91||Abstract:||
In this paper, a new approach to extract singular points in a fingerprint image is presented. It is usually difficult to locate the exact position of a core or a delta due to the noisy nature of fingerprint images. These points are the most widely used for fingerprint classification and matching. Image enhancement, thinning, cropping, and alignment are used for minutiae extraction. Based on the Poincaré curve obtained from the directional image, our algorithm extracts the singular points in a fingerprint with high accuracy. It examines ridge directions when singular points are missing. The algorithm has been tested for classification performance on the NIST-4 fingerprint database and found to give better results than the neural networks algorithm. Copyright © 2005 John Wiley & Sons, Ltd.
This paper was presented in " The IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2004). September 01 to September 03, 2004. Marbella, Spain. ".
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/2501||DOI:||10.1002/asmb.611||Ezproxy URL:||Link to full text||Type:||Journal Article|
|Appears in Collections:||Department of Computer Engineering|
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.