Fingerprint classification method based on binary image and core
基于二值图像中心点的指纹分类算法*

Fingerprint automated classification largely contributes to improving identification rate and detecting speed. Making an effective use of intrinsic fingerprint features like texture structure and texture orientation can increase the total of categories being classified. Classifying based on binary fingerprint image incompletely depended on accuracy of core, avoiding the interferential information of using the delta. Applying the ridge following method to classify fingerprint could follow the change of fingerprint ridge orientation.Fingerprints could be classified into 34 categories.