This paper presents a new approach to indexing videos of presentations which use electronic slides. By determining the images of slides in the video frames, and then matching the video sequences to the original electronic slides, the video can be indexed and searched, and the visual appearance of the segments can be improved. We first detect the "content area" in video frames using a color similarity weighted least square method. By monitoring the frame-to-frame "content difference", we then temporally segment the video into sequences which display the same slide. Since this differencing removes low-level imaging effects, we can then relate the video segments to slides by matching the content differences of adjacent video segments to the content differences of all possible slide pairs. By defining the transition probabilities of video segments, we are able to solve this matching efficiently in two steps, first by finding high likelihood matches, and then by using dynamic programming for the unmatched remainder. Once matched, the correspondence to the original slides can be used to enhance the presentation video quality in the content area, and can also be used for indexing and summarization. Experiments show high performance of segmentation and matching on several presentation videos which vary considerably in color and background style.