Optimum Multilevel Image Thresholding Based on Tsallis Entropy Method with Bacterial Foraging Algorithm
Multilevel image thresholding is an important operation in many
analyses which is used in many applications. Selecting correct
thresholds is a critical issue. In this paper, Bacterial Foraging
(BF) algorithm based on Tsallis objective function is presented
for multilevel thresholding in image segmentation. Experiments
to verify the efficiency of the proposed method and comparison
to Genetic Algorithm (GA) is presented. The experiment results
show that the proposed method gives the best performance in
multilevel thresholding. The method is also computationally
efficient, more stable and can be applied to a wide class of
computer vision applications, such as character recognition,
watermarking technique and segmentation of wide variety of
medical images.
Keywords: Multilevel thresholding, Bacterial foraging
algorithm, Tsallis objective function, image segmentation
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