Among possible research area in multimedia, keyframe extraction is an important topic that provides video summarization, faster browsing and accessing of wide video collections. In this paper, we propose a new automatic shot based keyframe extraction for video indexing and retrieval applications. Initially, the frames are sequentially clustered into shots by using feature extraction, continuity value construction steps of shot boundary detection process and the shot frame clustering technique. The cluster having a larger dispersion rate is selected for inter cluster similarity analysis (ICSA) and the sub-shot based keyframes are extracted using ICSA. The proposed shot boundary detection algorithm and video keyframe extraction technique are implemented and evaluated on publicly available ecological video datasets. Compared with existing related algorithms, our method yields better F1-score of 94.2% for shot boundary detection and better results for keyframe extraction. The keyframes extracted by the proposed method are used for video indexing and retrieval. © 2013 Elsevier B.V.