The Research Of Image Segmentation Technology Based On Edge Information

With development of computer, communication and information processing technologies, video-based applications show powerful extensibility. Video object segmentation aims to partition an image sequence into moving objects and to track the evolution of the moving objects along the time axis. Many applications related to video compression and transmission relies on video object segmentation Video object segmentation techniques are also important tools for content-based video coding and manipulation, and interactive multimedia applications. Video object segmentation usually divides the contents of a video frame into semantic regions that can be treated as objects. These semantically segmented objects can be coded so that object-based manipulation of video content can be realized in interactive multimedia applications. Although many researchers working in this field for many years, there is not one satisfying algorithm can process all sequence.This paper first presents the development and recent status of video object segmentation techniques, and the basic segmentation methods are discussed. In the following, this paper discusses the still image segmentation techniques with the emphasis on the analysis of methods of image smoothing and techniques of edge detection, and color image processing techniques are studied and simulated. Secondly, moving estimate theories of dynamic video segmentation techniques are described and the main video segmentation methods which called Snake model are discussed, and a detailed analysis on the external force of Snake model is made. Subsequently, the effects between GVF and traditional external force are compared and simulated in this paper. During the process of segmentation and extraction of video object, twi-difference algorithm is proposed in this paper combining the temporal-spatial information fusion and GVF-Snake algorithm, and the information capacity of traditional GVF-Snake algorithm is increased, it makes the initialization of video object more accurate, and improve the efficiency of segmentation and extraction of video object.