Histogram Based Split and Merge Framework for Shot Boundary Detection

  • D. S. Guru
  • Mahamad Suhil
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8284)

Abstract

In this paper, we propose a non-parametric approach for shot boundary detection in videos. The proposed method exploits the split and merge framework by the use of color histograms. Initially, every frame of the input video sequence undergoes color quantization and subsequently, the color histograms are computed for every quantized frame. The split and merge is driven by the fishers linear discriminant criterion function which results with a set of subsequences after several iterations which are assumed to be the shots present in the given video. The proposed method is experimentally tested on video samples from TrecVid 2002 dataset and YouTube online database. We have obtained overall accuracy of 85.5% Precision, 87.1% Recall and 86.1% F-measure for the dataset used. A comparative study of the proposed approach with the contemporary research works is also carried out.

Keywords

color quantization color histograms split and merge fishers linear discriminant analysis shot boundary detection 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • D. S. Guru
    • 1
  • Mahamad Suhil
    • 1
  1. 1.Department of Studies in Computer ScienceMysoreIndia

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