Algorithm of Moving Object Segmentation Based on Fuzzy Clustering
基于模糊聚类的运动对象分割算法研究

In order to obtain Integrated and consistent segmentation of motion video objects, the segmentation algorithm based on fuzzy clustering is used to obtain pixels that constitute boundaries of motion object and extract video objects in the sequence sequentially. The motion properties of the current frame in each wavelet sub-band first are calculated using information of current frame and some frames before it in this algorithm. The set of motion eigenvectors is constructed with these properties. Then, significant change pixels are separated by fuzzy C-mean clustering algorithm based on these motion eigenvectors of low-resolution image. The change detection mash of motion object is obtained with significant change image, instead of frame difference, by conventional method of change detection and video objects are extracted. At the same time, the mean absolute different between consecutive two frames is used to determine number of frames that are used for properties calculation. It ensures accuracy of video objects obtained,. The experimental results demonstrate the algorithm effective.