International Journal of Information Technology & Computer Science ( IJITCS )
This paper presents a proposed automatic fingerprint verification technique. The proposed technique consists of two phases; a training phase and a testing phase. In the training phase, firstly, image enhancement process is carried out using Adaptive Histogram Equalization (AHE) and Gabor filter, then, the Higher Order Statistics (HOS) of the image are estimated. The local and global features are extracting from each image or from its HOS. These features are used to train Support Vector Machines (SVMs) consisting of features database. In the testing phase, the features are extracted from every incoming image with or without image blurring or rotation and a feature matching step is performed to decide whether these features belong to the same person or not. The simulation results achieved up to 98 % verification rate and proved that the proposed technique can be used in a reliable way for automatic fingerprint verification in the presence of image blurring or rotation..
: Fingerprint Verification, SVMs, HOSs, Gabor Filter.
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