Authors: Rahul Malik
Addresses: School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India
Abstract: All of us are very well aware that identifying the information visually is more effective and efficient for human intelligence. In this aspect, one of the primary modes of interacting within and around for understanding the situation through images can act as crucial sources of information for the activities related to human intelligence. This paper's primary focus is to accomplish a better image processing impact using AI as part of image processing. Initially, this paper deals with introduction, elaboration, and mathematical representation on the essential theory of the ant colony algorithm. Furthermore, part of this paper deals with improvising the global search by introducing the crowding function of fish into the algorithm. Later, the improvised algorithm is utilised to segment the images to improve the impact of the segmentation process. Using this algorithm, the results demonstrate its feasibility, significant improvement in performance and the optimisation while segmenting the images.
Keywords: computer vision; image processing; ant colony algorithm; digital image; image segmentation; artificial intelligence algorithm.
International Journal of Computer Applications in Technology, 2021 Vol.65 No.3, pp.235 - 244
Received: 07 May 2020
Accepted: 23 Oct 2020
Published online: 19 Jun 2021 *