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Number 6

Color image segmentation using wavelet

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  • Samer kais Jameel and Ramesh R. Manza 2012. Color image segmentation using wavelet. International Journal of Applied Information Systems. 1, 6 (February 2012), 1-4. DOI=http://dx.doi.org/10.5120/ijais450134 
  • @article{10.5120/ijais2017451568,
author = {Samer kais Jameel  and Ramesh R. Manza},
title = {Color image segmentation using wavelet},
journal = {International Journal of Applied Information Systems},
issue_date = {February 2012},
volume = {1},
number = {},
month = {February},
year = {2012},
issn = {},
pages = {1-4},
numpages = {},
url = {/archives/volume1/number6/95-0134},
doi = { 10.5120/10.5120/ijais12-450134},
publisher = { xA9 2010 by IJAIS Journal},
address = {}
}

  • %1 450134
%A Samer kais Jameel 
%A Ramesh R. Manza
%T Color image segmentation using wavelet
%J International Journal of Applied Information Systems
%@ 
%V 1
%N 
%P 1-4
%D 2012
%I  xA9 2010 by IJAIS Journal

Abstract

In this paper, we discussed color image segmentation by extract the optimal features with which to discriminate between regions. Many real or texture images are made up of smooth regions and are best segmented using features in different areas. Schemas that select the optimal features for each pixel using wavelet analysis are proposed, leading to robust segmentation algorithm. Using two dimensions wavelet transforms to decompose the image into subbands channels and made up the of smooth image and convert the image into NTSC color space enables us to quantify the visual differences in the image, and then applies a clustering technique to partition the image into a set of “homogeneous” regions is also proposed.

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Keywords

Segmentation, color image, wavelet transform, k-means clustering

Index Terms

Computer Science
Information Sciences