A novel block intensity comparison code for video classification and retrieval

  • Authors:
  • M. Kalaiselvi Geetha;S. Palanivel;V. Ramalingam

  • Affiliations:
  • Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalainagar, Tamil Nadu 608 002, India;Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalainagar, Tamil Nadu 608 002, India;Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Annamalainagar, Tamil Nadu 608 002, India

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Appropriate organization of video databases is essential for pertinent indexing and retrieval of visual information. This paper proposes a new feature called block intensity comparison code (BICC) for video classification and retrieval. Block intensity comparison code represents the average block intensity difference between blocks of a frame. The extracted feature is further processed using principal component analysis (PCA) to reduce the redundancy while exploiting the correlations between the feature elements. The temporal nature of video is modeled by hidden Markov model (HMM) with BICC as the features. It is found that, BICC outperforms other visual features such as edge, motion and histogram which are commonly used for video classification.