A Shot Boundary Detection Technique Based on Local Color Moments in Ycbcr Color Space

Color moments are measures that can be used to differentiate images based on their color. Once computed, these moments provide a measure for color similarity between images. This color similarity can become a measure of finding difference between consecutive frames in a video. Finding the difference between temporally arranged frames in video is one of the issues in shot boundary detection which will segment the video in to meaningful units called shots. So a Shot boundary detection method based on primitives of color moments is proposed in this paper. The YCbCr color model is used for the experimentation. Each frame of the video is partitioned in to 8 X 8 smaller sub blocks. The first three color moments of every sub blocks of each frame in the video are computed. The feature vector is formed from the moments and compared between successive frames. The difference value higher than a predefined threshold at any pair of consecutive frames indicates the presence of a shot boundary between frames. By using YCbCr color space, the influence of illumination change and shadows is reduced. Experiments have been conducted on the standard soccer video database to evaluate the performance of the proposed method.