Segmentation of color images using genetic algorithm with image histogram

P. Sneha Latha; Pawan Kumar; Samruddhi Kahu; Kishor M. Bhurchandi

doi:10.1117/12.2180559

14 February 2015 Segmentation of color images using genetic algorithm with image histogram

P. Sneha Latha, Pawan Kumar, Samruddhi Kahu, Kishor M. Bhurchandi

Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 94450M (2015) https://doi.org/10.1117/12.2180559
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

This paper proposes a family of color image segmentation algorithms using genetic approach and color similarity threshold in terns of Just noticeable difference. Instead of segmenting and then optimizing, the proposed technique directly uses GA for optimized segmentation of color images. Application of GA on larger size color images is computationally heavy so they are applied on 4D-color image histogram table. The performance of the proposed algorithms is benchmarked on BSD dataset with color histogram based segmentation and Fuzzy C-means Algorithm using Probabilistic Rand Index (PRI). The proposed algorithms yield better analytical and visual results.

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P. Sneha Latha, Pawan Kumar, Samruddhi Kahu, and Kishor M. Bhurchandi "Segmentation of color images using genetic algorithm with image histogram", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450M (14 February 2015); https://doi.org/10.1117/12.2180559

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KEYWORDS

Image segmentation

Genetic algorithms

Image processing algorithms and systems

Color image processing

RGB color model

Visualization

Image processing

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