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This paper presents a novel method for fingerprint ROI (region of interest) segmentation using Fourier coefficients computed over non-overlapping image segments and used to train a neural network. Experimental results, obtained using a publicly available test database of 200 fingerprint image, demonstrate that this method outperforms a pixel-based approach, in all three figures of merit.
This paper proposes ANN based method for fingerprint ROI (Region of Interest) segmentation. Proposed ANNs where trained with 10000 samples extracted from 20 fingerprint images (in grey-scale and binary modes). The experimental results, including three statistical performance indicators, shows very good performance of the proposed method on a test database of 200 fingerprint images.
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