Image clustering using Zernike moments and self-organizing maps for gastrointestinal tract
Computer Science and Information Systems, Tome 22 (2025) no. 3
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Typically, the image features are compared to find the similarity among the images in a content-based image clustering system. However, images with high feature similarity may be different from each other in terms of semantics. Hence, this paper proposes a novel algorithm based on unsupervised neural classifier systems for in-vivo image clustering to address the semantic gap issue. The visual features are represented using Wavelet transform and Zernike moments, and a self-organizing map is utilized for the clustering of images. The algorithm-based prototype system is trained for categorizing gastral images in the respective clusters as per the similarity. The system can be used to segment images with automatic noise reduction and rotation invariances for given images. Experiments are performed on the real gastrointestinal images obtained from a known gastroenterologist, and the results using Daubechies Wavelet Transform + Zernike Moments on LUV color scheme yield 88.3% accuracy.
Keywords:
Machine learning, Self-organizing maps, Zernike moments, Wavelet transforms, Gastroenterology
Parminder Kaur; Avleen Malhi Malhi; Husanbir Singh Pannu. Image clustering using Zernike moments and self-organizing maps for gastrointestinal tract. Computer Science and Information Systems, Tome 22 (2025) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2025_22_3_a5/
@article{CSIS_2025_22_3_a5,
author = {Parminder Kaur and Avleen Malhi Malhi and Husanbir Singh Pannu},
title = {Image clustering using {Zernike} moments and self-organizing maps for gastrointestinal tract},
journal = {Computer Science and Information Systems},
year = {2025},
volume = {22},
number = {3},
url = {http://geodesic.mathdoc.fr/item/CSIS_2025_22_3_a5/}
}
TY - JOUR AU - Parminder Kaur AU - Avleen Malhi Malhi AU - Husanbir Singh Pannu TI - Image clustering using Zernike moments and self-organizing maps for gastrointestinal tract JO - Computer Science and Information Systems PY - 2025 VL - 22 IS - 3 UR - http://geodesic.mathdoc.fr/item/CSIS_2025_22_3_a5/ ID - CSIS_2025_22_3_a5 ER -
%0 Journal Article %A Parminder Kaur %A Avleen Malhi Malhi %A Husanbir Singh Pannu %T Image clustering using Zernike moments and self-organizing maps for gastrointestinal tract %J Computer Science and Information Systems %D 2025 %V 22 %N 3 %U http://geodesic.mathdoc.fr/item/CSIS_2025_22_3_a5/ %F CSIS_2025_22_3_a5