Performance evaluation of color image segmentation using K means clustering and watershed technique

Author

Vij, Saumya ; Sharma, Shantanu ; Marwaha, Chetan

Author_Institution

Dept. of Comput. Sci., Guru Nanak Dev Univ., Amritsar, India

fYear

2013

fDate

4-6 July 2013

Firstpage

1

Lastpage

4

Abstract

Image segmentation is a key technology in image processing which partition an image into its constituent regions. Watershed and k means segmentation techniques are practical approaches for color image segmentation. This paper discusses quantitative evaluation measures for color image segmentation based on these techniques. Color image segmentation can be viewed as an extension of gray level image segmentation. Quantitative measures like discrete entropy, root mean square error, visible color difference are proposed for color images.

Keywords

image colour analysis; image segmentation; pattern clustering; color image segmentation; discrete entropy; gray level image segmentation; image processing; k means clustering; k means segmentation technique; performance evaluation; quantitative evaluation measures; root mean square error; visible color difference; watershed segmentation technique; Clustering algorithms; Color; Entropy; Histograms; Image color analysis; Image segmentation; Root mean square; Discrete entropy; K means segmentation; Root mean square error; Watershed segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communications and Networking Technologies (ICCCNT),2013 Fourth International Conference on

Conference_Location

Tiruchengode

Print_ISBN

978-1-4799-3925-1

Type

conf

DOI

10.1109/ICCCNT.2013.6726560

Filename

6726560