Edge detection is one of the basic operation carried out in image processing and object identification .In this paper, we present a distributed Canny edge detection algorithm that results in significantly reduced memory requirements, decreased latency and increased throughput with no loss in edge detection performance as compared to the original Canny algorithm. The new algorithm uses a low-complexity 8-bin non-uniform gradient magnitude histogram to compute block-based hysteresis thresholds that are used by the Canny edge detector. Furthermore, an FPGA-based hardware architecture of our proposed algorithm is presented in this paper and the architecture is synthesized on the Xilinx Spartan-3E FPGA. Simulation results are presented to illustrate the performance of the proposed distributed Canny edge detector. The FPGA simulation results show that we can process a 512×512 image in 0.28ms at a clock rate of 100 MHz.
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[v1] 2014-05-07 01:37:39
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