Journal
OPTOELECTRONICS LETTERS
Volume 13, Issue 2, Pages 151-155Publisher
TIANJIN UNIV TECHNOLOGY
DOI: 10.1007/s11801-017-7014-9
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Funding
- National Natural Science Foundation of China [61401425]
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In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independent of the ship target size is constructed by combining the shape feature with ship histogram of oriented gradient (S-HOG) feature, and the target can be recognized by AdaBoost classifier. As demonstrated in our experiments, the proposed method with the detection accuracy of over 96% outperforms the state-of-the-art method. efficiency switch and modulation.
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