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Color image segmentation using wavelet

Samer kais Jameel , Ramesh R. Manza Published in Signal Processing

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
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  1. Samer Jameel and Ramesh R Manza. Article: Color image segmentation using wavelet. International Journal of Applied Information Systems 1(6):1-4, February 2012. BibTeX

    	author = "Samer kais Jameel and Ramesh R. Manza",
    	title = "Article: Color image segmentation using wavelet",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 1,
    	number = 6,
    	pages = "1-4",
    	month = "February",
    	note = "Published by Foundation of Computer Science, New York, USA"


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