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Shape Descriptor Based on Centroid with Chord Lengths for Image Retrieval

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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))

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Abstract

Shape is considered as a significant characteristic in object detection. In applications such as recognizing the shapes and classification, retrieval of shapes, extraction of shape features and their depiction plays an important role. We propose a shape descriptor which is computationally economical, compact and fast. In this work, we present three methods of feature computation based on chords. Among three, good result is obtained by the third method. Since the proposed work is based on centroid involving a global histogram, shape descriptor is invariant to all transformations. When compared to other shape signatures the proposed shape descriptor resulted in bull’s eye score of 84.56% on MPEG-7 dataset.

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Authors and Affiliations

  1. S D M College of Engineering and Technology, Dharawad, India

    Jayadevi Karur & Jagadeesh Pujari

Authors
  1. Jayadevi Karur
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  2. Jagadeesh Pujari
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Corresponding author

Correspondence to Jayadevi Karur .

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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Karur, J., Pujari, J. (2019). Shape Descriptor Based on Centroid with Chord Lengths for Image Retrieval. 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_15

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_15

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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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