Optimal Multilevel Image Thresholding to Improve the Visibility of Plasmodium sp. in Blood Smear Images

摘要

Malaria is one of the mosquito-borne communicable diseases for humans caused due to Plasmodium sp. During the treatment process, it is necessary to identify the exact Plasmodium sp. in order to give the specific antimalarial drug. Hence, in this paper, an image segmentation procedure is attempted to enhance the visibility of the Plasmodium sp. in microscopic blood smear images. In this paper, two RGB blood smear images of Plasmodium ovale (300 × 300) are considered and segmented using Otsu and heuristic algorithms, such as PSO, DPSO, and FODPSO available in the literature. During the segmentation procedure, maximization of a multiple objective function is adopted to guide the heuristic algorithm-based exploration. The performances of considered algorithms are analyzed using the popular image parameters, such as Otsu's function, SSIM, RMSE, and PSNR. This study shows that FODPSO offers improved segmentation result compared to PSO and DPSO algorithms. The similar procedure can be used to identify other Plasmodium sp. using the microscopic blood smear images.