Eminent scene change detection algorithm and new indexing method for video retrieval on MPEG sequences

Abstract

We propose an eminent scene change detection (SCD) algorithm, and also present a new video-indexing method for fast content-based browsing and retrieval in video databases. The first step in our approach is to extract representative frames by using the proposed SCD algorithm from the Motion Picture Experts Group (MPEG) video sequence. Thereafter, we perform the video indexing by applying the rosette pattern (RP) to the extracted representative frames, and retrieve them. A principal cause of these processing procedures is that the performance of video indexing and retrieval system depends on the SCD. And how accurately SCD performs as well as a preprocessing are some of the considerations that we must take into account. Therefore, we classify every possible scene change that may happen within the video into three types: abrupt, gradual, and flashlight. And we detect every kind of scene change. Our SCD algorithm is better than the conventional ones in terms of SCD performance and we demonstrate its superiority by experiments. We also extract representative frames that represent series of detected scenes by the proposed accumulative histogram intersection measure (AHIM). Finally, we apply the RP to extracted representative frames for indexing, we can remarkably reduce the number of pixels (NOP) required to index and excellently retrieve the video scene. (C) 2002 Society of Photo-Optical Instrumentation Engineers.