<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/14137" mdate="2010-08-24 00:00:00"> <author>Zeinab Zeinalpour-Tabrizi and Faeze Asdaghi and Mahmooh Fathy and Mohammad Reza Jahed-Motlagh</author> <title>Gradual Shot Boundary Detection and Classification Based on Fractal Analysis</title> <pages>1358 - 1363</pages> <year>2010</year> <volume>4</volume> <number>8</number> <journal>International Journal of Computer and Information Engineering</journal> <ee>https://publications.waset.org/pdf/14137</ee> <url>https://publications.waset.org/vol/44</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>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 AISbased classifier. Proposed features are &amp;amp;ldquo;vertical intercept&amp;amp;quot; and &amp;amp;ldquo;fractal dimension&amp;amp;quot; 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. </abstract> <index>Open Science Index 44, 2010</index> </article>