Color Image Edge Detection Research-Image Edge Detection Research And Application

Digital image processing is a technology that using computer as a tool to solve image information. Generally speaking,image information is the main source that people get and exchange information from it. Therefore the application of image processing technology inevitably involve in every domain and aspects of people's ordinary life. Nowadays image processing technology has brought great benefits to humans'society culture and economy. We can believe that this technology will have greater improvement in the domain of theory innovation in the coming soon and will play an indispensable part in the area of humans'society,scientific research and economy activities. As human knowledge's extending, image processing technology must be have a lasting and widely advancement.As to a specific aspect of image processing technology, people are only interested in some parts, we call them foregrounds. The rest called backgrounds. The techniques and the processes to divide the image into several parts which have different features and to pick up foreground are called image segmentation. On the other hand, the boundaries of the foregrounds are the edges we are interested in. Once these edges are detected, the foregrounds are picked up. These edge based image segmentation also called edge detection.In the beginning,this thesis will introduce some concepts of color image segmentation and edge detection methods briefly. Based on the discussion of color space, we introduce the concept of clustering analysis.first we use bilateral filter to preprocess the input image,then using the vector order statistics and Otsu method,this paper develop a new color image edge detection method,using this method, we firstly got the R,G,B components'edge intensity respectively,then we analyze these information by implying the Non-maxima suppressiong, after all the pixels are processed,we integrate the three components'information and the edge map are generated. Simulation results show that this algorithm guarantees the color image edge's continuity and accuracy successfully.Region-based and Histogram-based segmentation approaches have been widely used in image segmentation. Difficulties arise when we use these techniques. To provide efficient algorithms that not only produce better segmentation results but also maintain low computational complexity, an improved image segmentation method based on region-based histogram dividing and maximum fuzzy entropy is proposed in this paper. This algorithm also integrates the advantage of traditional top-down segmentation method. Experiments show that this method can get satisfied result after processing.