Vitorino Ramos: Map Segmentation by Colour Cube Genetic K-Mean Clustering

31. Vitorino Ramos, Fernando Muge, Map Segmentation by Colour Cube Genetic K-Mean Clustering, Proc. of ECDL´2000 - 4th European Conference on Research and Advanced Technology for Digital Libraries, J. Borbinha and T. Baker (Eds.), ISBN 3-540-41023-6, Lecture Notes in Computer Science, Vol. 1923, pp. 319-323, Springer-Verlag -Heidelberg, Lisbon, Portugal, 18-20 Sep. 2000.

Vitorino Ramos - Genetic Algorithms in Image Segmentation

Vitorino Ramos - Genetic Algorithms in Image Segmentation

Figures - One original image (left - Luanda, Angola map) and two segmentation examples, rivers and roads respectively (Low resolution images).

PDF file: paper (118 Kb)

Abstract: Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum number of segmentation areas in an image when it contains similar and/or unstationary texture fields. In this work, a method is described for evolving adaptive procedures for these problems. In many real world applications data clustering constitutes a fundamental issue whenever behavioural or feature domains can be mapped into topological domains. We formulate the segmentation problem upon such images as an optimisation problem and adopt evolutionary strategy of Genetic Algorithms for the clustering of small regions in colour feature space. The present approach uses k-Means unsupervised clustering methods into Genetic Algorithms, namely for guiding this last Evolutionary Algorithm in his search for finding the optimal or sub-optimal data partition, task that as we know, requires a non-trivial search because of its NP-complete nature. To solve this task, the appropriate genetic coding is also discussed, since this is a key aspect in the implementation. Our purpose is to demonstrate the efficiency of Genetic Algorithms to automatic and unsupervised texture segmentation. Some examples in Colour Maps are presented and overall results discussed.

Keywords: Genetic Algorithms, Colour Image Segmentation, Classification, Clustering, Image Analysis and Processing.

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º Omran, M., Engelbrecht, A.P., Salman, A., "Particle Swarm Optimization method for Image Clustering", in International Journal of Pattern Recognition and Artificial Intelligence, Vol. 19, Issue 3, pp. 297-321, May 2005.

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º L.T. Law, Y.M. Cheung, Color Image Segmentation Using Rival Penalized Controlled Competitive Learning, Proc.of 2003 International Joint Conference on Neural Networks (IJCNN'2003), Portland, Oregon, USA, July 20-24, 2003.

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