Color Reduction in RGB based on Bacteria Foraging Optimization

Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for distributed optimization and control. BFOA is inspired by the social foraging behavior of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. The underlying biology behind the foraging strategy of E.coli is emulated in an extraordinary manner and used as a simple optimization algorithm. It’s an optimization used for tackling complex search problems of the real world. The scientists have been drawing inspiration from nature and natural creatures for years. Bacterial Foraging Optimization is a burgeoning nature inspired technique for finding 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. Keywords— Quantization, Bacteria Foraging Optimization, Swim, Tumble, Chemo-tactic, CMC, SI.