Abstract

Image segmentation is one of the essential tasks in the field of computer vision. This paper proposes a new image segmentation approach based on Fuzzy C Means (FCM) and Ant Lion Optimization (ALO). FCM has the ability to represent ambiguous information in a more robust way. Bio-inspired algorithms such as ALO have the ability to find optimal parameters in search spaces. These characteristics of FCM and ALO have been utilized in this paper for improving image segmentation. The proposed hybrid FCM-ALO based image segmentation is compared with Otsu-thresholding based image segmentation using the publicly available image segmentation dataset images. The experiment results show that the proposed method is comparatively better for almost all the images.

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