For the last few years, shot boundary detection has been recognized as an important research issue on video retrieval. Also, as a preliminary step for the task, it is essential to extract salient features from videos. Recently, it has become common to perform the two tasks in the compressed domain to alleviate their computational costs. In this paper, we propose a novel shot boundary detection technique, which uses two feature images, DC and edge image, which are extracted directly from MPEG compressed video. While a DC image can be easily obtained, edge image extraction usually requires a considerable computational burden. For fast edge image extraction, we suggest us of only a few AC coefficients of each DCT block, in motion compensated P-frames, B-frames, and I-frames. This drastically reduces the computational burden, compared to edge extraction in the spatial domain. In order to further reduce the computational burden, another edge image extraction technique is also suggested on the basis of AC prediction, using DC images. By using the edge energy diagram, obtained from edge images, and histograms from DC images, shot boundaries, such as abrupt transitions, fades, and dissolves are detected automatically. Simulation results show that the proposed techniques are fast and effective.