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Performance Comparison of Clustering Algorithms Based Image Segmentation on Mobile Devices

  • Hemantkumar R. Turkar
  • Nileshsingh V. Thakur
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 768)

Abstract

In general, clustering concept is used for segmentation of images. In literature, it is found that different clustering approaches are proposed for the purpose of image segmentation. This paper presents comparative analysis of clustering algorithms namely, k-Means (KM), Moving k-Means (MKM), and Enhanced Moving k-Means (EMKM) for image segmentation on mobile devices. Experimentations are carried out on natural images with RGB and HSV color spaces which are used in mobile devices. Performance of KM, MKM, EMKM algorithms is evaluated using qualitative and quantitative parameters, particularly, using Mean Square Error. The obtained results show that the EMKM algorithm is the most suitable technique for image segmentation .

Keywords

Clustering algorithm RGB HSV Image segmentation 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Hemantkumar R. Turkar
    • 1
  • Nileshsingh V. Thakur
    • 2
  1. 1.Department of Computer Science and EngineeringRajiv Gandhi College of Engineering and ResearchNagpurIndia
  2. 2.Department of Computer Science and EngineeringNagpur Institute of TechnologyNagpurIndia

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