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International Conference on Recent Trends in Image Processing and Pattern Recognition

RTIP2R 2016: Recent Trends in Image Processing and Pattern Recognition pp 305–316Cite as

Shot-Based Keyframe Extraction Using Bitwise-XOR Dissimilarity Approach

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 709))

Abstract

Keyframe extraction is an essential task in many video analysis applications such as video summarization, video classification, video indexing and retrieval. In this paper, a method of extracting keyframes from the shots using bitwise XOR dissimilarity has been proposed. The task of segmenting continuous video into shots and selection of key frames from segmented shots has been addressed. The above task has been accomplished through a feature extraction technique, based on bitwise XOR operation between consecutive gray scale frames of the video. Thresholding mechanism is employed to segment the videos into shots. Dissimilarity matrix is constructed to select a representative keyframe from every shot of a video sequence. The proposed shot boundary detection and keyframe extraction approach is implemented and evaluated on a subset of TRECVID 2001 data set. The proposed approach outperform other contemporary approaches in terms of efficiency and accuracy. Also, the experimental results on the data set have demonstrated the efficacy of the proposed keyframe extraction technique in terms of fidelity measure.

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Author information

Authors and Affiliations

  1. DoS in Computer Science, University of Mysore, Mysore, 570 006, India

    Rashmi B.S. & Nagendraswamy H.S.

  2. Karnataka State Open University, Mysore, India

    Rashmi B.S.

Authors
  1. Rashmi B.S.
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  2. Nagendraswamy H.S.
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Corresponding author

Correspondence to Rashmi B.S. .

Editor information

Editors and Affiliations

  1. The University of South Dakota, Vermillion, South Dakota, USA

    K.C. Santosh

  2. Karnatak Arts, Science and Commerce College, Bidar, India

    Mallikarjun Hangarge

  3. Polytecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  4. University of Hyderabad, Hyderabad, India

    Atul Negi

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© 2017 Springer Nature Singapore Pte Ltd.

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B.S., R., H.S., N. (2017). Shot-Based Keyframe Extraction Using Bitwise-XOR Dissimilarity Approach. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_28

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  • DOI: https://doi.org/10.1007/978-981-10-4859-3_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4858-6

  • Online ISBN: 978-981-10-4859-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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