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Smart Trends in Computing and Communications pp 487–496Cite as

Multi-level Thresholding and Quantization for Segmentation of Color Images

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 165))

Abstract

Image segmentation is a complex problem, in particular to color images. Different mechanisms exist for the gray-level image segmentation, but a very less work exists for the color image segmentation. Thresholding is the technique which is, in general, used for the gray-level image segmentation. This paper presents an approach for the color image segmentation using the thresholding logic. This paper describes the mechanism to find the multi-level thresholds in view of color image segmentation. The presented procedure uses the histogram to find the multi-level thresholds. Weights, mean, variance and within-class variance are used to find the multi-level thresholds. Experimentations are carried out on the BSD color image dataset.

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Author information

Authors and Affiliations

  1. JSPM’s Babasaheb Naik College of Engineering, Pusad, India

    Shailesh T. Khandare

  2. Nagpur Institute of Technology, Nagpur, India

    Nileshsingh V. Thakur

Authors
  1. Shailesh T. Khandare
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  2. Nileshsingh V. Thakur
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Corresponding author

Correspondence to Shailesh T. Khandare .

Editor information

Editors and Affiliations

  1. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  2. Department of Computer Science and Engineering, University of Kalyani, Kalyani, India

    Jyotsna Kumar Mandal

  3. Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand

    Chakchai So-In

  4. Nagpur Institute of Technology, Nagpur, Maharashtra, India

    Nileshsingh V. Thakur

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Cite this paper

Khandare, S.T., Thakur, N.V. (2020). Multi-level Thresholding and Quantization for Segmentation of Color Images. In: Zhang, YD., Mandal, J., So-In, C., Thakur, N. (eds) Smart Trends in Computing and Communications. Smart Innovation, Systems and Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-15-0077-0_50

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