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Edge is one of basic traits of image, it contains some important information, for example place of image, figure and so on. Thence, edge detection is an important process of image processing and analyze. Edge detection is the foundation technology of image processing that contains image measuring, image segmentation, image compressing, and image recognition, so it is very important. There are many classic methods about edge detection that based on differential coefficient, for example, Sobel operator based grads, Prewitt operator, Robert operator, Laplace operator, LOG operator, Canny operator and so on. Now there are some new methods, such as statistical, edge connecting, edge detection based on micro-wavelet. However, these methods only use in some limitation area. Through analyze merits and drawbacks of these methods,and then create a new edge detection which based on mathematical morphology.Firstly,present definition of digital image,image detection and its functions and significance. Secondly, present some classic and new edge detection methods, and then summarize their merits and drawbacks by experiments. In succession, summarize basic knowledge and properties of binary morphology and gray morphology, and clarify purposes of these morphology operators in image processing. Finally, create a new edge detection method based on existent mathematical morphology. Multi-scale and multi-frame frame elements are used in the method. The method that improves those traditional methods, can detect better edge details, and can resist salt and pepper noise and Gaussian noise, and it is easy and useful. The method based on mathematical morphology which is a combination of multi-scale and multi-structure structure elements. It is good for image edge detection.
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