THRESHOLD SEGMENTATION USING MODIFIED 2D-OTSU PSO ALGORITHM

Abstract

Median filter is a technique which applied to remove impulse noise in image processing. Filtered images are carried out to the next level of operations, such as segmentation and object recognition, etc. In this study chili x-ray images are taken for analysis. The chili x-ray images were preprocessed using existing algorithms such as Average filter, Median filter, Wiener filter, Gamma intensity correction and CLAHE, and proposed algorithms such as 4-connected Median filter, weighted 4-connected median filter and Optimized connected Median filter using PSO. Texture regions are extracted by gabor filter. From the extracted texture regions Modified Range filter along with Adaptive Particle Swarm Optimization were applied to extract textures. To perform the next level operation such as segmentation, fixed threshold and Otsu threshold with PSO were applied. However seeds and fungus affected portions of chili x-ray images were not clear. To overcome the above problem this research paper proposes a well-organized algorithm and it is known as modified 2-D Otsu PSO algorithm. It performs better than the previous threshold algorithms. Performance measures are taken to prove that the proposed algorithm works better than the previous methods.