基于支持向量机的多目标分类和识别

支持向量机(SVM)算法广泛应用于模式识别等领域,但是SVM最初是针对二类别分类提出,在多分类识别中稍显逊色。对将SVM由二分类扩展到多分类的算法进行了研究,发现有向无环图(DAG-SVM)是其中用的最多的算法之一。因此,针对军事领域图像的多目标分类,选择有向无环图算法来实现军事图像中单兵、装甲、低空等多目标的分类识别。

Multi Target Classification and Recognition Based on Support Vector Machine

Support Vector Machine(SVM),which was developed for binary classification initially, now is widely used in many research fields like pattern recognition. However,its application to multi-classification is inefficient. This paper did research on the extension algorithms of SVM from binary classification to multi-classification,and found that Directed Acyclic Graph(DAG-SVM)is one of the most popularly used. Therefore,this paper focuses on its application of multi-classification in military area,and achieves recognition of many military objects,such as soldiers,armored cars,low altitude targets,and so on.