Over the last few years, the amount of video data has increased significantly. So, the necessity of video summarization has reached a new level. Video summarization is summarizing a large video with a fewer number of frames keeping the semantic content same. In this paper, we have proposed an approach which takes all the frames from a video and then shot boundaries are detected using the color moment and SURF (Speeded Up Robust Features). Then the redundancy of the similar frames is eliminated using the color histogram. Finally, a summary slide is generated with the remaining frames which are semantically similar to the total content of the original video. Our experimental result is calculated on the basis of a questionnaire-based user survey which shows on average 78% positive result whereas 3.5% negative result. This experimental result is quite satisfactory in comparison with the existing techniques.