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Biomedical Image Fusion &Segmentation using GLCM

Published on None 2011 by Madhusmita Sahoo
2nd National Conference on Computing, Communication and Sensor Network
Foundation of Computer Science USA
CCSN - Number 1
None 2011
Authors: Madhusmita Sahoo

Madhusmita Sahoo . Biomedical Image Fusion &Segmentation using GLCM. 2nd National Conference on Computing, Communication and Sensor Network. CCSN, 1 (None 2011), 34-39.

author = { Madhusmita Sahoo },
title = { Biomedical Image Fusion &Segmentation using GLCM },
journal = { 2nd National Conference on Computing, Communication and Sensor Network },
issue_date = { None 2011 },
volume = { CCSN },
number = { 1 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 34-39 },
numpages = 6,
url = { /specialissues/ccsn/number1/4170-ccsn008/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Special Issue Article
%1 2nd National Conference on Computing, Communication and Sensor Network
%A Madhusmita Sahoo
%T Biomedical Image Fusion &Segmentation using GLCM
%J 2nd National Conference on Computing, Communication and Sensor Network
%@ 0975-8887
%N 1
%P 34-39
%D 2011
%I International Journal of Computer Applications

In this paper we present a new fusion technique to increase the information content of the fused image. We propose information fusion by maximizing the wavelet entropy using windowing technique. It helps to diagnose the diseases like tumor, cancer …etc effectively. The images are decomposed by wavelet transform and using maximum selection rule the low frequency and high frequency bands are fused. After fusion The entropy is maximized using windowing technique. Using IDWT the fused image is resulted. The affective area in fused image is isolated and analyzed using GLCM based segmentation. GLCM based segmentation preserves the discontinuity and edge information better than other segmentation techniques.

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Index Terms

Computer Science
Information Sciences


Image fusion Wavelet Transform MS rule GLCM