Bi-level thresholding using PSO, Artificial Bee Colony and MRLDE embedded with Otsu method

Sushil Kumar, Pravesh Kumar Tomar, Tarun Kumar Sharma, Millie Pant

Abstract: Image segmentation is required to be studied in detail some particular features (areas of interest) of a digital image. It forms an important and exigent part of image processing and requires an exhaustive and robust search technique for its implementation. In the present work we have studied the working of MRLDE, a newly proposed variant of differential evolution combined with Otsu method, a well known image segmentation method for bi-level thresholding. The proposed variant, termed as Otsu+MRLDE, is tested on a set of 10 images and the results are compared with Otsu method and some other well known metaheuristics.