Abstract
Ant colony optimization algorithm (ACO) which performs well in discrete optimization has already been used widely and successfully in digital image processing. Slow convergence, however, is an obvious drawback of the traditional ACO. A quantum ant colony algorithm (QACO), based on the concept and principles of quantum computing can overcome this defect. In this study, a QACO-based edge detection algorithm is proposed. Quantum bit (qubit) and quantum rotation gate are introduced into QACO to represent and update the pheromone respectively. Experiments and comparisons show that QACO is an efficient and effective approach in image edge detection.
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