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Image edge is the most fundamental image feature and it includes the position and contour of the image. Image edge feature extraction has been widely applied in the image analysis and processing such as feature description, image segmentation, image enhancement and pattern recognition. This paper studies the characteristics of Sobel operator, Prewitt operator, Laplacian operator and other conventional operators in edge detection in details, processes the same image with these operators respectively, compares the strengths and weaknesses of these traditional operators in edge detection and proposes a multi-operator fusion method for image edge feature extraction according to the characteristics of change of local gray-level difference along the image edge, namely that gray-level changes slightly along edge direction while it changes greatly along the direction vertical to the edge. The experiment proves that the method of this paper improves the ability to extract detail information of the image edges and to suppress false edges and provides an effective approach for the practical image processing.

An Image Edge Feature Extraction Method Based on Multi-operator Fusion