Ajay Sharma
Computer Science
June 2022
ACO is experienced with pondering picture edge detection problems in order to advance the edge data already available in the image, which is essential to understanding the image's content. Finding good visits using the excellent input provided by the ant pheromone update is the core component of ACO. Ant colony optimisation obtains approximations of solutions to the challenging problem by utilising the food-gathering strategies used by ant social organisations. Edge detection is a key component of image processing. It mostly participates in computer vision and image analysis' pre-processing stage. It generally recognises the contour of an image and provides important details about a picture. Hence, it reduces the quantity of material that has to be processed for high-level processing tasks like object recognition and picture segmentation. The most important step in edge detection is threshold setting since it decides whether or not a valid edge map will be produced. In this study, edge detection is the purpose of ant colony optimisation, which is inspired by ant colonies (ACO).
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