Image segmentation through index images

Image segmentation is an important preprocessing step in the applications of MPEG-4 and computer vision. It is one of major challenges in MPEG-4, since MPEG-4 is constrained by how well previous segmentation is accomplished. We propose a scheme called the SII (segmentation through index images) algorithm for image segmentation. We use the histograms of index images as the features to classify the image data into several clusters for segmentation. The 1st-moment index image is the low-resolution image that is its pixels value which is the codevector index to label all corresponding image blocks. Through the 2nd-moment index image, we identify image blocks which belong to contour or homogeneous blocks. Then, we can connect all homogeneous blocks which have the same label to define the interior of a region. The contour block is split into a smaller size and assigned to one of its neighboring regions to obtain a more accurate contour of objects. We present several experiments to show the efficiency of our SII algorithm. According to simulation results, our SII algorithm is effective for image segmentation