Feature Extraction with Thinning Algorithms for Precise Cretoscopy

The surge of technology and information has led to the need to escalate the protection of data. The security codes and pins are in jeopardy due to the profuse increase of hacking. A diacatholicon for authenticity is provided by verifying and identifying each person. Fingerprints have proved to be impressive and flawless with a gargantuan number of users. The existing work has dealt with the traditional methods of processing and matching fingerprints. The proposed work deals with enhancement and algorithms for thinning and minutiae extraction. The texture features such as energy, correlation coefficient and entropy have been implemented to accredit the thinning process. Three fingerprint images are taken for processing and comparison. Thinning algorithms such as Zhang-Suen’s and Hall’s have been used. The minutiae are unsheathed by the Crossing number and Summing up algorithms. The simulation results of the algorithms have been compared, and the precision rates of fingerprints have been procured.