STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Image Processing & Pattern Recognition Progress

Hardware/Software Co-Simulation of Gradient-based Edge Detectors: A Comparative Study

  1. Kazi Ahmed Asif Fuad
  2. Shahriyar Masud Rizvi

Abstract

Edge detection, a segmentation technique, produces an edge map that contains important information about the image. We realized Gradient-based Edge Detection Algorithms in FPGA hardware utilizing Hardware-Software Co-Simulation with the help of Simulink (Mathworks) and System Generator (Xilinx). We explored and utilized different gradient based edge detection operators Sobel-Fieldman, Robert and Prewitt Operator. After comparative analysis, we found both Sobel and Robert operators among the best with hardware realization of Robert operator utilizing less resources (LUT & Flip-Flops). All the algorithms were synthesized for Spartan-6 LX16 FPGAs from Xilinx.

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