Research Article Open Access

Shot Detection Using Genetic Edge Histogram and Object Based Video Retrieval Using Multiple Features

R. Kanagavalli1 and K. Duraiswamy2
  • 1 Anna University, India
  • 2 KS Rangasamy College of Technology, India
Journal of Computer Science
Volume 8 No. 8, 2012, 1364-1371

DOI: https://doi.org/10.3844/jcssp.2012.1364.1371

Submitted On: 5 June 2012 Published On: 3 August 2012

How to Cite: Kanagavalli, R. & Duraiswamy, K. (2012). Shot Detection Using Genetic Edge Histogram and Object Based Video Retrieval Using Multiple Features. Journal of Computer Science, 8(8), 1364-1371. https://doi.org/10.3844/jcssp.2012.1364.1371

Abstract

As the usage of multimedia data increasing rapidly, how to get the video data we need efficiently become so important. Recent advances in multimedia technologies allow the capture and storage of video data with relatively inexpensive computers. Problem Statement: However, without appropriate search techniques all these data are hardly usable. Users want to query the content instead of the raw video data. Today research is focused on video retrieval. Content-based search and retrieval of video data becomes a challenging and important problem. To retrieve the content of the video the user need automatic classification and categorization of the visual content. Approach: In this study a novel algorithm is proposed for shot detection using Genetic Edge Histogram and 2-D discreate cosine transform as a feature and multiple features like color, motion, shape and SIFT are used to retrieve the similar shots. Results and Conclusion: The combination of proposed features yields good results interms of precision and recall.

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Keywords

  • Video retrieval
  • feature extraction
  • SIFT
  • shot detection