Abstract
Digital image segmentation is often used as a preprocessing step in image analysis where different objects in the image need to be separated. One of the most used techniques for image segmentation is multilevel thresholding. Different criteria are used for determination of optimal thresholds, but in all cases, multilevel thresholding is a hard optimization problem that cannot be solved by deterministic methods. Swarm intelligence stochastic optimization metaheuristics have been proven to be very successful for such problems. In this chapter, we propose adjusted guided fireworks algorithm (GFWA) for multiple optimal threshold determination based on Kapur's entropy, Otsu's criteria and Tsallis' entropy. Comparison with other state-of-the-art techniques shows that the GFWA exhibits superior performance.
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