facial skin segmentation using bacterial foraging optimization algorithm

Nowadays, analyzing human facial image has gained an ever?increasing importance due to its various applications. imagesegmentation is required as a very important and fundamental operation for significant analysis and interpretation of images. amongthe segmentation methods, image thresholding technique is one of the most well?known methods due to its simplicity, robustness, andhigh precision. thresholding based on optimization of the objective function is among the best methods. numerous methods exist forthe optimization process and bacterial foraging optimization (bfo) is among the most efficient and novel ones. using this method,optimal threshold is extracted and then segmentation of facial skin is performed. in the proposed method, first, the color facial imageis converted from rgb color space to improved hue?luminance?saturation (ihls) color space, because ihls has a great mappingof the skin color. to perform thresholding, the entropy?based method is applied. in order to find the optimum threshold, bfo is used.in order to analyze the proposed algorithm, color images of the database of sahand university of technology of tabriz, iran wereused. then, using otsu and kapur methods, thresholding was performed. in order to have a better understanding from the proposedalgorithm; genetic algorithm (ga) is also used for finding the optimum threshold. the proposed method shows the better results thanother thresholding methods. these results include misclassification error accuracy (88%), non?uniformity accuracy (89%), and theaccuracy of region’s area error (89%).