JOURNAL ARTICLE

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

Puneet RaiMaitreyee Dutta

Year: 2013 Journal:   International Journal of Computer Applications Vol: 68 (15)Pages: 5-9

Abstract

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 value.This paper proposes an improved method based on heuristic which assigns weight to the neighborhood.Experimental results are provided to support the superior performance of the proposed approach.

Keywords:
Ant colony optimization algorithms Computer science Heuristics Enhanced Data Rates for GSM Evolution Artificial intelligence Optimization algorithm Metaheuristic Mathematical optimization Mathematics

Metrics

6
Cited By
1.89
FWCI (Field Weighted Citation Impact)
20
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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