JOURNAL ARTICLE

Image Edge Detection Based on Ant Colony Optimization Algorithm

Huan Yin

Year: 2016 Journal:   International Journal of Advanced Pervasive and Ubiquitous Computing Vol: 8 (1)Pages: 1-12   Publisher: IGI Global

Abstract

Ant colony optimization (ACO) is a new heuristic algorithm which has been proven a successful technique. The article applies the ACO to the image edge detection, get edge image edge according to different neighborhood access policy through MATLAB simulation, and use the best neighborhood strategy to get detection. Compared with the traditional edge detection methods, the algorithm can effectively suppress the noise interference, retain most of the effective information of the image.

Keywords:
Ant colony optimization algorithms Edge detection Enhanced Data Rates for GSM Evolution Computer science Heuristic MATLAB Image (mathematics) Noise (video) Image edge Interference (communication) Deriche edge detector Algorithm Artificial intelligence Computer vision Image processing

Metrics

4
Cited By
0.00
FWCI (Field Weighted Citation Impact)
6
Refs
0.11
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

Related Documents

© 2026 ScienceGate Book Chapters — All rights reserved.