Optimal Multi- Level Thresholding for Color Image Using Kapur’s Entropy and Bacterial Foraging Algorithm
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 5
Abstract
This paper presents, a multi-thresholding approach for a class of 481 x 321 sized standard colour test images using Kapur’s entropy function and Bacterial Foraging Optimization (BFO) optimization algorithm. In this work, maximization of the Kapur’s entropy is chosen as the cost function and the BFO algorithm is allowed to explore the RGB histogram, till the threshold value is attained. The performance of the classical BFO algorithm is also enhanced using Brownian Walk (BW) strategy. The capability of BFO assisted segmentation with Kapur’s function is validated in association with Particle Swarm Optimization (PSO) and classical BFO algorithms using Kapur’s entropy value and search iteration taken by the algorithm. Proposed approach also confirmed using the image quality measures, such as RMSE, PSNR, SSIM, NAE and NCC.
Authors and Affiliations
R. Arthisree, S. Abinaya, R. Ashwini, V. Sweatha
Keywords
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