Statistical pattern recognition for real-time image edge detection on FPGA

Image edge detection is a fundamental process in computer vision. Image edges represent the major fraction of information in an image. Traditional edge-detection techniques focus on the gradient calculation method. In this paper, for the first time, the statistical pattern recognition method is used to detect the edge after the real-time image was processed via the median filtering method and implemented on FPGA. In comparison to the Sobel algorithm, the proposed method has superior anti-noise capability.