红外与激光工程, 2016, 45 (1): 0104004, 网络出版: 2016-04-05   

基于SVM分类的红外舰船目标识别

Infrared ship-target recognition based on SVM classification
作者单位
天津津航技术物理研究所,天津 300192
摘要
针对海天背景下红外舰船目标识别提出了一种基于机器学习的分类算法。该算法首先利用分割算法提取红外图像中的连通区域,并对原图相应的位置进行标记和归一化处理,然后利用HOG特征提取标记区域的高维特征向量,用线下样本库训练得到的SVM分类器对所提取的HOG特征进行高维特征空间的分类,识别目标和干扰。仿真实验表明,该算法具有良好的性能,在复杂海天干扰背景下能够有效地识别红外舰船目标。
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.

张迪飞, 张金锁, 姚克明, 成明伟, 吴永国. 基于SVM分类的红外舰船目标识别[J]. 红外与激光工程, 2016, 45(1): 0104004. 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): 0104004.

本文已被 14 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!