Application Of The Improved Watered Arithmetic At Image Segmentation

In image research and application, people usually interested in some region of image, which is often called target or foreground (the others is called background). It generally indicates the specific region with special property in the image. In order to identify and analyze the target in the image, separation of the region from the image is needed. Based on which, people can measure the target and utilize the image more.In this thesis, the characteristic of digital image is represented, and the application of morphology in image segmentation is discussed. Edge detection is studied base on morphological method. Several typical algorithms of image segmentation are investigated. Watershed algorithm of image segmentation is a classical and effective method. It gets attentions because of getting quick and effective and right result. Watershed algorithms is an automatic segmentation scheme to generate closed outlines, which might give rise to over-segmentation, i.e. numerous small segmented closed regions that blur the target contours or shapes. This paper proposed an improved watershed algorithm based on morphological and clustering method, In the first place we deal with the image using morphological method and then the three-stage improved watershed algorithm we proposed in this article, At last define the characteristic vector for every watershed region, On the basis of the comparison between the vector and its neighbor region's vector, We can gain the segmented image by clustering regions according to the similarity vectors, Also the image quality can be improved by the optimization of vision impression, Experiment results show that the algorithm is available and useful.