Research Of Video Object Segmentation Algorithm Based On SOFM

With the rapid development of multimedia technologies and emergence of 2G video coding, the technology of video motional object segmentation, significant part of multimedia application, will be applied to such fields as video coding, retrieval, browsing, smart video surveillance, virtual reality, computer vision, pattern recognition and multimedia communication based on object, widely in the future. However, no general method to video motional object segmentation is accepted and presently, scenes can be divided into many semantic objects and coded by content-based representation and scalability that will be playing an important role in 2G technologies of video coding and segmentation.Video segmentation is to divide an image or sequence into some areas according to the specifications in order to extract some significant entities, called video object in digital video processing. The technology of video motional object steps from that of still image segmentation and it includes two categories mainly: interframe-based segmentation and intraframe-based segmentation. Firstly, the original image data is reduced to segmentation, which can be implemented, by low-pass filters and media filters, etc; secondly, features of image data, i.e. color component, texture, motion, frame difference and semantic information will be extracted; thirdly, the determination to segmentation with some uniform standard is made based on the features.Artificial neural network (ANN) is an active and crossing discipline and research on it is of significance, which is composed of a multitude of neurons connected mutually to simulate the properties of human brain. Its information processing is achieved by the function among different neurons connected and the storage of information and knowledge is represented by the physical contacts of network components. ANN has been adopted to classify and cluster image and video data.