Title: EFFICIENT FINGERPRINT CLASSIFICATION USING SINGULAR POINT

Issue Number: Vol. 1, No. 3
Year of Publication: 2011
Page Numbers: 611-616
Authors: Ali Ismail Awad, Kensuke Baba
Journal Name: International Journal of Digital Information and Wireless Communications (IJDIWC)
- Hong Kong

Abstract:


Singular point is one of the local fingerprint features, and it is used as a landmark due its scale and rotation immutability. Singular point charac- teristics have been widely used as a feature vector for many fingerprint classification approaches. This paper introduces a new fingerprint classi- fication method which utilizes a singular point as a reference point to part an input image. The key idea of the proposed classification method is di- viding fingerprint into small sub-images using singular point location, and then, creating distinguished patterns for each class using frequency domain representation for each sub-image. The performance evaluation has been conducted for the singular point detection method and the proposed clas- sification algorithm with different database. Both the processing time and the classification accuracy are considered as key issues of the classification approach. The experimental work shows that the achieved classification ac- curacy over FVC2002 database subsets is up to 83:7% with considerable processing time and robustness to scale, shift, and rotation.