Double change detection method for moving-object segmentation based on clustering

In this paper, an efficient moving object segmentation algorithm in the wavelet domain is proposed using three successive frames. The change detection method, which employs fuzzy C-means clustering technique to classify motion features of four wavelet sub-bands, is used twice to separate significant change pixels in the wavelet domain from the background. After applying the intersect operation, the change detection masks are obtained in wavelet domain. Finally, further object shape information and accurate extraction of the moving object is obtained in original resolution according to current object edge map. The experimental results demonstrate the algorithm effective.