Abstract
Next to DNA, fingerprint is the unique feature which identifies the individual. Distortions and skin deformations makes the fingerprint unreliable and it is difficult to match using minutiae alone. But when ridge features are incorporated with minutiae features (minutiae type, orientation and position) more topological information can be obtained. And also ridges are invariant to transformations such as rotation and translation[1]. Ridge based coordinate system is used to extract the ridge features such as ridge length, ridge count, ridge type and curvature direction in the skeletonized image. Breadth First Search is used to traverse the graph formed using the minutiae as the node and the ridge vector formed using the ridge features as the edge. The proposed ridge feature gives additional information for fingerprint matching with little increment in template size and can be used along with the existing minutiae features to increase the accuracy and robustness of fingerprint recognition systems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Signal & Image Processing : An International Journal
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
