Different Edge Detection Algorithms Comparison and Analysis on Handwritten Chinese Character Recognition

Abstract

The acquired image will has different levels of noise pollution and image distortion in Handwritten Chinese character recognition document image processing. For these situations the accurate and fast edge detection method is an important prerequisite for the recognition results. The widely used edge detection algorithms such as: first derivative-based edge detection method, second derivative edge detection method, canny operator, mathematical morphology edge detection and fuzzy edge detection method. In this paper according to our database of handwritten Chinese characters a lot of experiments to compare the excellent of various algorithms in the field of Chinese character handwriting recognition application. These algorithms are sensitive to image noise and we nowadays discuss new edge detection for the theory of wavelet edge detection method and genetic algorithms. According to our experimental results we explore the new edge detection method to improve the edge detection, image segmentation accuracy and quickness.