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Color Image Quantization based on Bacteria Foraging Optimization
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 25 - Number 7 |
| Year of Publication: 2011 |
| Authors: Rajinder Kaur, Akshay Girdhar, Surbhi Gupta |
10.5120/3042-4130
|
Rajinder Kaur, Akshay Girdhar, Surbhi Gupta . Color Image Quantization based on Bacteria Foraging Optimization. International Journal of Computer Applications. 25, 7 ( July 2011), 33-42. DOI=10.5120/3042-4130
Abstract
Bacterial Foraging Optimization (BFO) is optimization technique proposed by K. M. Passino in 2002 To tackle complex search problems of the real world, scientists have been drawing inspiration from nature and natural creatures for years. Bacterial Foraging Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. A Color images Quantization is necessary if the display on which a specific image is presented works with less colors than the original image. While a lot of color reduction techniques exist in the literature, they are mainly designed for image compression as they tend to alter image color structure and distribution, the researchers are always finding alternative strategies for color quantization so that they may be prepared to select the most appropriate technique for the color quantization. The objective of this research work, is to implement a new algorithm for Color Image Quantization based on Bacteria Foraging Optimization. To compare the designed algorithm with other swarm intelligence techniques and to validate the proposed work. The proposed algorithm is then applied to commonly used images including the phantom images. The conducted experiments indicate that proposed algorithm generally results in a significant improvement of image quality compared to other well-known approaches.
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