An ant-inspired algorithm for detection of image edge features

This paper presents a technique inspired by swarm methodologies such as ant colony algorithms for processing simple and complicated images. It is shown that the proposed technique for image processing is capable of performing feature extraction for edge detection and segmentation, even in the presen...

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Veröffentlicht in:Applied soft computing Jg. 11; H. 8; S. 4883 - 4893
Hauptverfasser: Etemad, S. Ali, White, Tony
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.12.2011
Schlagworte:
Ant colony systems
Feature extraction
Image edge analysis
Feature extraction
Image edge analysis
Ant colony systems
ISSN:1568-4946, 1872-9681
Online-Zugang:Volltext
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Zusammenfassung:This paper presents a technique inspired by swarm methodologies such as ant colony algorithms for processing simple and complicated images. It is shown that the proposed technique for image processing is capable of performing feature extraction for edge detection and segmentation, even in the presence of noise. Our proposed approach, Ant-based Correlation for Edge Detection (ACED), is tested on different samples and the results are compared to typical established non-swarm-based methods. The comparative analysis highlights the advantages of the proposed method which generates less distortion when noise is added to the test images. Both qualitative and quantitative evaluations support the claim, confirming the significance of our swarm-based method for image feature extraction and segmentation.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2011.06.011