Singular Point Detection for Efficient Fingerprint Classification
A singular point or singularity on fingerprint is considered as a fingerprint landmark due its scale, shift, and rotation immutability. It is used for both fingerprint classification and alignment in automatic fingerprint identification systems. This paper presents a comparative study between two singular point detection methods available in this paper. The comparative study has been conducted on the Poincaré index and the complex filter methods, and it aims to catch the optimum singular point detection method in terms of the processing time and the detection accuracy. Moreover, discovering the processing time bottlenecks for both methods is an advanced step to improve the their performance.