الفهرس | Only 14 pages are availabe for public view |
Abstract Iris is touch-less automated real-time biometric system for user authentication. Pattern recognition approaches suffer from high cost, long development times, and computationally intensive. General Purpose Systems are low speed and not portable ; FPGA-based system prototype implemented by using VHDL language. Iris recognition system is, implemented in software. To overcome the problems of obtaining a real-time decision of the human iris in an accurate, robust, low complexity, reliable, and fast technique. Threshold concepts are used to segment the pupil. Canny edge detector and Circular Hough Transform are used to localize the iris region. Rubber Sheet Model is used as an unwrapping and normalization algorithm. Histogram equalization technique is used to enhance the normalized iris image contrast. Iris features are extracted and encoded using 1D log-Gabor transform and the DCT respectively. Finally, the template matching is performed using the Hamming distance operator. Experimental tests on the CASIA (version 1) database achieved 98.94708% of recognition accuracy using 1D Log-Gabor with Equal Error Rate (EER) equal to 0.869%. The FAR and FRR are 0% and 1.052923% respectively. In contrast, 93.07287% of accuracy using DCT with EER equal to 4.485%. The FAR and FRR are 0.886672% and 6.040454%, respectively. The proposed approach (FDCT-based feature extraction and Hamming Distance stages) are implemented and synthesized using Xillinx FPGA chip (XC3S1200E-4fg320), occupying 1% of chip CLBs. It achieved 58.88 μs to process and takes a decision compared with current software implemented taking 1.926794 s. A 1D log-Gabor iris recognition system is more accurate and secure. However, DCT-based one is more reliable, having a low computational cost and a good interclass separation in a minimum time. The hardware implementation is small and fast enough. |