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Validating Few Contemporary Approaches in Image Segmentation – A Quantitative Approach

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Advances in Signal Processing and Intelligent Recognition Systems (SIRS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 968))

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Abstract

In this paper, we present an extensive study and quantitative evaluation of six segmentation techniques on images of Berkeley Segmentation Database. Image segmentation plays a vital role in many computer vision applications and benchmarking such algorithms may assist research community in present and future research efforts in the field of image segmentation. Color space models, Hybrid color space and wavelet, Gradient Magnitude Techniques, K – means, C-Means & Fuzzy C-Means (FCM) and Edison’s Mean – shift approaches are evaluated using at least six metrics with respect to ground-truth boundaries of entire images in BSD 300/500 dataset images. The results stated here gives useful insights to above mentioned approaches and its significance in aligning upcoming research avenues in image segmentation.

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Author information

Authors and Affiliations

  1. Blackbuck Engineers Pvt Ltd, Hyderabad, India

    Syed Fasiuddin

Authors
  1. Syed Fasiuddin
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Correspondence to Syed Fasiuddin .

Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology and Management, Kerala, India

    Sabu M. Thampi

  2. Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA

    Oge Marques

  3. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

    Sri Krishnan

  4. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

    Kuan-Ching Li

  5. University of Naples Federico II, Naples, Italy

    Domenico Ciuonzo

  6. Electrical Engineering Department, Indian Institute of Technology Patna, Patna, India

    Maheshkumar H. Kolekar

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Fasiuddin, S. (2019). Validating Few Contemporary Approaches in Image Segmentation – A Quantitative Approach. In: Thampi, S., Marques, O., Krishnan, S., Li, KC., Ciuonzo, D., Kolekar, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2018. Communications in Computer and Information Science, vol 968. Springer, Singapore. https://doi.org/10.1007/978-981-13-5758-9_34

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  • DOI: https://doi.org/10.1007/978-981-13-5758-9_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5757-2

  • Online ISBN: 978-981-13-5758-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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