• Infrared and Laser Engineering
  • Vol. 45, Issue 1, 104004 (2016)
Zhang Difei*, Zhang Jinsuo, Yao Keming, Cheng Minwei, and Wu Yongguo
Author Affiliations
  • [in Chinese]
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    DOI: 10.3788/irla201645.0104004 Cite this Article
    Zhang Difei, Zhang Jinsuo, Yao Keming, Cheng Minwei, Wu Yongguo. Infrared ship-target recognition based on SVM classification[J]. Infrared and Laser Engineering, 2016, 45(1): 104004 Copy Citation Text show less

    Abstract

    Aiming at the ship-target recognition of sea-sky background, an classification algorithm based on machine learning was proposed. In the method, the segmentation algorithm was firstly adopted to extract connected region in infrared image. Then, the corresponding position of the original image was marked and normalized. Afterwards, the high-dimensional feature vector of branded region by using the HOG algorithm was extracted. Finally, the high-dimensional feature vector that came form suspected target area was classified by the SVM classifier which was trained by sample library. Simulation experimental result indicates that the algorithm not only can effectively recognise the infrared ship-targets in complex sea-sky background of interference, but also have good performance.
    Zhang Difei, Zhang Jinsuo, Yao Keming, Cheng Minwei, Wu Yongguo. Infrared ship-target recognition based on SVM classification[J]. Infrared and Laser Engineering, 2016, 45(1): 104004
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