Image feature extraction based multiple ant colonies cooperation

Zhilong Zhang; Weiping Yang; Jicheng Li

doi:10.1117/12.2176542

22 May 2015 Image feature extraction based multiple ant colonies cooperation

Zhilong Zhang, Weiping Yang, Jicheng Li

Author Affiliations +

Proceedings Volume 9476, Automatic Target Recognition XXV; 947615 (2015) https://doi.org/10.1117/12.2176542
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

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.

Citation Download Citation

Zhilong Zhang, Weiping Yang, and Jicheng Li "Image feature extraction based multiple ant colonies cooperation", Proc. SPIE 9476, Automatic Target Recognition XXV, 947615 (22 May 2015); https://doi.org/10.1117/12.2176542

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