Implementation Of A Fpga-Arm-Based Canny Edge Detection System

Canny edge detection is widely used in image processing. Conventional Canny edge detection is commonly realized in CPUs, GPUs or FPGA fabrics alone, but CPUs and GPUs are not suitable for low-power applications. And existing edge detection implementations on specific FPGA model have little compatibility with other models. In this paper, we propose an effective Canny edge detection system consist of FPGA and ARM-SoC. ARM core is embedded with Yocto Linux OS, and FPGA is in charge of image processing and VGA display. FPGA IP cores are designed to communicate through Avalon-ST Bridge. In the end, the system has been implemented and tested with a quantity of images. The testing results show the efficiency of the proposed system design scheme and the system can be based on to achieve more complex algorithm.