A Method of Scene Boundary Detection for Indexing Video Data Efficiently

In a cell animation, a background scene is presented with one cell. When animation scenes are changed, a relatively large scene change occurs because their backgrounds are also changed. Unlike a camera-based real movie, a cell animation is made in the way of manual drawing. For this reason, such animation does not use many colors. In order to apply the characteristics of animations as most as possible and detect a scene change of a cell animation effectively, this study proposes a new scene change detection technique with the stepwise use of the color and block-based histograms. The proposed algorithm receives continuous animation images as input, changes the RGB color space into the HSI color space, executes the difference operation of color values of the two images, and thereby primarily determines whether the neighboring images are scene change candidates. If they are judged to be scene change candidates, the color histogram for each sub-region is made, and then a weight value is applied to finally determine whether a scene change occurs. To compare the proposed scene change detection method with conventional scene change detection methods, the block-based scene change detection method and the histogram-based scene change detection method as conventional ones were implemented. In this study, to qualitatively evaluate the performance of the proposed method of detecting scene boundaries, the accuracy measure was defined. The two conventional algorithms are not complicated relatively and are widely used to extract a scene change. The experiment of this study reveals that the proposed method more accurately detects an animation scene change than other conventional methods. The proposed animation scene boundary detection method is expected to be applied usefully to the fields of digital video data indexing and retrieval, dynamic motion analysis, and other related areas.