A Novel Algorithm for Key Frames Selection

The main objective of this study framework is to help the user to management the interesting video images from the huge storage device. The study can be divided into three main steps is listing as follows: shot boundary detection, key frame selection and evaluation method are designed by analyzing the video content. In this paper we proposed a novel algorithm for shot boundary detection. First, transform the RGB color model into LUV color model according our experimental results. The useful features of each frame are extracted from sequence images by the automatically computation of their color moment-preserving and matching 64-predefined bit planes in order to detect the shot boundary. The excellent shot boundary detection will result in the good key frames selection. Second, the key frame selection is proceed by applying the geometric invariant moments which successful be used in target tracing, pattern recognition, and facial recognition. In our experiments we used five test sequences that belong to five different program categories: movies, advertising, sport game, news, and commercial documentary. The experimental results showed that our method is feasible, effective, and is better than the former approaches.