Abstract
In this paper a novel approach is proposed to detect reference point for fingerprint images. Reference point extraction is a key component in automatic fingerprint identification and recognition systems. A new method was proposed for fingerprint reference point extraction, based on field flow curve and clustering. High curvature points in the flow curves are used in our reference point detection. Because we use flow curve instead of ridge for reference point detection, our method is robust to noise and has a good result on fingerprint image with low quality. Also our method has the ability to detect a reference point for an arch class fingerprint which is hard for other methods to detect it. The experiments are conducted on FVC2002-DB2a and FVC2004 to measure the performance of our reference point detection. Experimental results show that our algorithm is robust and it has better results than other approaches.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
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.