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Proceedings Paper

Image feature extraction based multiple ant colonies cooperation
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Paper Abstract

This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.

Paper Details

Date Published: 22 May 2015
PDF: 11 pages
Proc. SPIE 9476, Automatic Target Recognition XXV, 947615 (22 May 2015); doi: 10.1117/12.2176542
Show Author Affiliations
Zhilong Zhang, National Univ. of Defense Technology (China)
Weiping Yang, National Univ. of Defense Technology (China)
Jicheng Li, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 9476:
Automatic Target Recognition XXV
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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