Abstract
ABSTRACT Flower pollination-based algorithm (FPA), inspired from the pollination process of flowers, is a population-based metaheuristic optimisation algorithm for solving real-world problems. This article introduces the feature of insectivorous plants in catching the pollinators (preys) with the solution procedure of FPA for avoiding sub-optimal traps and models the dental image segmentation problem as an optimisation problem. This enhanced FPA (EFPA) is then applied in solving the formulated multilevel segmentation problem of dental images. The proposed EFPA-based method optimises the threshold values for dental images by effectively exploring the problem space. The segmented images along with PSNR values of the proposed method are compared with FPA-based and OTSU-basedsegmentation methods for exhibiting its superior performance.
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