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Content Based Video Retrieval Using SURF, BRISK and HARRIS Features for Query-by-image

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Book cover Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1035))

Abstract

Content Based Video Retrieval (CBVR) is an approach for retrieving most relevant videos from the video database. Applications of CBVR are increasing day by day. This paper uses Speeded up Robust Feature (SURF), Binary Robust Invariant Scalable Key Points (BRISK) and HARRIS corner Detector to retrieve the similar videos. Our proposed system firstly identifies the key frames from the video using color Histogram method. In this method the color component is used to identify the key Frame. Next, above said three features are derived from all the videos in database. The three features are also calculated for the query image. By using similarity matching techniques, all the features are jointly used to assign rankings to the videos in the database based on the features of query image. The videos having ranks below threshold can be retrieved as most relevant videos to the query image given.

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Author information

Authors and Affiliations

  1. VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India

    Tejaswi Potluri

  2. VFSTR, Guntur, India

    Nitta Gnaneswara Rao

Authors
  1. Tejaswi Potluri
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  2. Nitta Gnaneswara Rao
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Corresponding author

Correspondence to Tejaswi Potluri .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Potluri, T., Gnaneswara Rao, N. (2019). Content Based Video Retrieval Using SURF, BRISK and HARRIS Features for Query-by-image. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_24

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_24

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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