AI augmentation in the field of digital image processing

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.