Image Edge Detection Based On Mathematical Morphology And Wavelet Transform

Edge is an important feature of the image, edge detection is a digital image segmentation, object recognition, shape extraction region, and is very important foundation for the field of image analysis.The research on edge detection has a long history, and there have been lots of methods proposed for it. But all of the methods for edge detection still have some drawbacks and advantages. It is hard to propose a general method of edge detection applied to all images. Because, It is crucial that edge and noise are in the high frequency region of image. And It is inevitable that the image details will be removed, when de-noising. Therefore, edge detection is still a hot and difficult currently. So the main research orientation of edge detection is to make improvements to existing methods or to find new methods for edge detection with requirements.The paper is organized as following five parts. Chapter one gives an introduction of the significance and development of the field of edge detection. In chapter two, firstly, it gives an introduction of the preprocessing method, and a new method based on anistropic diffusion equation is proposed. Then it introduces classical edge detection algorithm, and proposes a new fusion edge detection method based on the improved Sobel operator and Canny operator, and gives edge detection results of these methods and offers some relative analysis and comparison. The chapter three offers the basic theory of morphological edge detection and traditional edge detection operators. Meanwhile, a new morphological detection operator is constructed and combined with the diffusion equation, which is detecting edge from the perspective of multi-dimensional and more structure. In the chapter four, at first, it gives an introduction of the basic theory of wavelet transformation and edge detection method of maximum value of wavelet. Then, it is combined with anistropic diffusion equation and morphological operators, and detecting edge, and comparing with the proposed method by experiment results. At last, the paper ends with a conclusion and some further research plans mentioned in chapter five.