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18th International Conference on Pattern Recognition (ICPR'06) Volume 4
Analysis of Abnormality in Endoscopic images using Combined HSI Color Space and Watershed Segmentation
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
ASCII Text
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B.V. Dhandra, Ravindra Hegadi, Mallikarjun Hangarge, V. S. Malemath, "Analysis of Abnormality in Endoscopic images using Combined HSI Color Space and Watershed Segmentation," Pattern Recognition, International Conference on, vol. 4, pp. 695-698, 18th International Conference on Pattern Recognition (ICPR'06) Volume 4, 2006.
 
 
BibTex
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@article{ 10.1109/ICPR.2006.268,
author = {B.V. Dhandra and Ravindra Hegadi and Mallikarjun Hangarge and V. S. Malemath},
title = {Analysis of Abnormality in Endoscopic images using Combined HSI Color Space and Watershed Segmentation},
journal ={Pattern Recognition, International Conference on},
volume = {4},
year = {2006},
issn = {1051-4651},
pages = {695-698},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.268},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Analysis of Abnormality in Endoscopic images using Combined HSI Color Space and Watershed Segmentation
SN - 1051-4651
SP695
EP698
A1 - B.V. Dhandra,
A1 - Ravindra Hegadi,
A1 - Mallikarjun Hangarge,
A1 - V. S. Malemath,
PY - 2006
KW - null
VL - 4
JA - Pattern Recognition, International Conference on
ER -
 
B.V. Dhandra, Gulbarga University, India.
Ravindra Hegadi, Gulbarga University, India.
Mallikarjun Hangarge, Gulbarga University, India.
V. S. Malemath, Gulbarga University, India.
In this paper, a method for detecting possible presence of abnormality in the endoscopic images is presented. The pre-processed endoscopic color images are segmented in the HSI color space. The pixels in the input color image corresponding to the segmented image are extracted for further processing. This image is smoothened using average filter and converted into grayscale image. Its inverse transform is obtained for further processing and extended minima is imposed on the processed image using morphological reconstruction. Then the morphological watershed segmentation is carried out on this image and the number of regions is counted and is compared with the threshold value. If the number of regions is more than the threshold value, then the output image is an indicative of possible presence of abnormality in the image.
Citation:
B.V. Dhandra, Ravindra Hegadi, Mallikarjun Hangarge, V. S. Malemath, "Analysis of Abnormality in Endoscopic images using Combined HSI Color Space and Watershed Segmentation," icpr, vol. 4, pp.695-698, 18th International Conference on Pattern Recognition (ICPR'06) Volume 4, 2006
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