Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset., {"references":["S. W. Smoliar and H.-J. Zhang, \"Content-based video indexing and\nretrieval,\" IEEE Multimedia, vol. 1, no. 2, 1994, pp. 62-72.","R. Lienhart, S. Pfeiffer, and W. Effelsberg, \"Video abstracting,\"\nCommun. ACM, vol. 40, no. 12, 1997, pp. 55-62.","X. U. Cabedo and S. K. Bhattacharjee, \"Shot detection tools in digital\nvideo,\" in Proc. Non-Linear Model based Image Analysis, 1998,\npp.121-126.","V. Kobla, D. DeMenthon, and D. 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