In this paper, a novel method to generate video summaries is proposed, which is allocated mainly for being applied to on-line videos. The novelty of this approach lies in the fact that the authors of this paper transfer the video summarization problem to a single query image retrieval problem. This approach utilizes the recently proposed Compact Composite Descriptors (CCDs) and a fuzzy classifier. In particular, all the video frames are initially sorted according to the distance between an artificially generated, video depended, image. Then the ranking list is classified into a preset number of clusters using the Gustafson Kessel fuzzy classifier. The video abstract is calculated by extracting a representative key frame from every cluster. A significant characteristic of the proposed method is its ability to classify the frames of the video into one or more clusters. Experimental results are presented to indicate the effectiveness of the proposed approach.