SOM and fuzzy based color image segmentation

Authors:
Ahmad Khan;M. Arfan Jaffar;Tae-Sun Choi
Affiliations:
National University of Computer & Emerging Sciences, Islamabad, Pakistan;National University of Computer & Emerging Sciences, Islamabad, Pakistan and Gwangju Institute of Science & Technology, Gwangju, Korea;Gwangju Institute of Science & Technology, Gwangju, Korea
Venue:
Multimedia Tools and Applications
Year:
2013

Citing 16
Cited 1

Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations

IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive segmentation with Intelligent Scissors

Graphical Models and Image Processing
Normalized Cuts and Image Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Organizing Maps

Self-Organizing Maps
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying

IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift Analysis and Applications

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
What Energy Functions Can Be Minimizedvia Graph Cuts?

IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation

International Journal of Computer Vision
Lazy snapping

ACM SIGGRAPH 2004 Papers
"GrabCut": interactive foreground extraction using iterated graph cuts

ACM SIGGRAPH 2004 Papers
An Integrated Framework for Image Segmentation and Perceptual Grouping

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Multiobjective genetic algorithm-based fuzzy clustering of categorical attributes

IEEE Transactions on Evolutionary Computation
Color image segmentation using histogram thresholding - Fuzzy C-means hybrid approach

Pattern Recognition
CTex—An Adaptive Unsupervised Segmentation Algorithm Based on Color-Texture Coherence

IEEE Transactions on Image Processing

Editorial: advanced semantic and social multimedia technologies for future computing environment

Multimedia Tools and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Spatial information enhances the quality of clustering which is not utilized in the conventional FCM. Normally fuzzy c-mean (FCM) algorithm is not used for color image segmentation and also it is not robust against noise. In this paper, we presented a modified version of fuzzy c-means (FCM) algorithm that incorporates spatial information into the membership function for clustering of color images A progressive technique based on SOM is used to automatically find the number of optimal clusters. The results show that our technique outperforms state-of-the art methods.