Title :
SVM-based Fingerprint Classification Using Orientation Field
Author :
Ji, Luping ; Yi, Zhang
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Beijing
Abstract :
This paper presents a classification method of fingerprint using orientation field and support vector machines. It estimates orientation field through pixel gradient, then calculates the percentages of the directional block classes. These percentages are combined as a four dimensional vector, by which the trained hierarchical classifier classifies the fingerprint into one of the six classes it belongs to. Experiments show that this method has high classification accuracy as well as low computational time cost.
Keywords :
fingerprint identification; image classification; support vector machines; SVM-based fingerprint classification; computational time cost; directional block classes; orientation field; pixel gradient; support vector machines; Classification algorithms; Computational efficiency; Computational intelligence; Computer science; Fingerprint recognition; Laboratories; Partitioning algorithms; Pattern matching; Support vector machine classification; Support vector machines;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.700
