Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics

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Image Edge Detection using Modified Ant Colony Optimization Algorithm based on Weighted Heuristics

Ant Colony Optimization (ACO) is nature inspired algorithm based on foraging behavior of ants. The algorithm is based on the fact how ants deposit pheromone while searching for food. ACO generates a pheromone matrix which gives the edge information present at each pixel position of image, formed by ants dispatched on image. The movement of ants depends on local variance of image’s intensity val...

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Image Edge Detection Based on Ant Colony Optimization Algorithm

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Noisy images edge detection: Ant colony optimization algorithm

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

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noisy images edge detection: ant colony optimization algorithm

the edges of an image define the image boundary. when the image is noisy, it does not become easy to identify the edges. therefore, a method requests to be developed that can identify edges clearly in a noisy image. many methods have been proposed earlier using filters, transforms and wavelets with ant colony optimization (aco) that detect edges. we here used aco for edge detection of noisy ima...

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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 detectio...

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ژورنال

عنوان ژورنال: International Journal of Computer Applications

سال: 2013

ISSN: 0975-8887

DOI: 10.5120/11653-7158