A new approach for template matching in digital images using an Artificial Bee Colony Algorithm

Abstract

In this paper, we applied the artificial bee colony algorithm (ABC) to the object recognition in the images. ABC is a new metaheuristics approach inspired by the collective and individual foraging behavior of honey bee swarm. The objective is to find a pattern or reference image (template) of an object somewhere in a target landscape scene, considering that it may be translated, scaled, rotated and/or partially occluded. This will result in location of the given reference image in the target landscape image. Results of the experiments with grayscale and color images show that the ABC is faster than other evolutionary algorithms and with comparable accuracy.