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Sea target detection based on SVM method using HSV color space

机译:基于HSV颜色空间的SVM方法的海目标检测。

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Sea target detection is an important goal for military purposes and navigation. A new supervised clustering method is introduced for optimum classification which is based on the Support Vector Machine (SVM) classifier. Utilizing color features for sea target detection was not considered seriously in previous works. In this paper, the SVM is utilized for classification and color features are applied to train this classifier. For obtaining the best results, the training samples are extracted from the HSV color space. The superiority of the new method to the relative previous works is conspicuous.
机译:海上目标检测是军事目的和航行的重要目标。引入了一种新的监督聚类方法,用于基于支持向量机(SVM)分类器的最佳分类。在以前的工作中,没有认真考虑将颜色特征用于海目标检测。在本文中,支持向量机用于分类,而色彩特征则用于训练该分类器。为了获得最佳结果,从HSV颜色空间中提取训练样本。新方法相对于先前的相关工作的优越性是显而易见的。

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