Grey Scale Histogram based Image Segmentation using Firefly Algorithm

Abstract

In the present work, optimal multi-level image segmentation is proposed using the Firefly Algorithm (FA). RGB histogram image is considered for both bi-level and multi-level segmentation. Multithresholding is used to enhance the information such as intensity, pixels of images based on the chosen threshold. In this work, heuristic algorithm based multi-thresholding such as Otsu’s thresholding and Kapur’s entropy function is implemented for Gray scale test images. Proposed technique are validated for mostly used benchmark images and the outcome of these algorithms are validated for already determined quality measures which is existing in the literature. The Performance of the gray scale images on Firefly Algorithm is carried out using these parameters, like objective value, PSNR, SSIM. From this paper, it is observed that, the considered heuristic algorithms are efficient to extract the information of image based on the chosen threshold values.

Keywords

Gray scale test image; Segmentation; Otsu; Kapur’s function; Firefly Algorithm; Image

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