基于HOG特征和SVM分类器的红外图像智能检测与分类方法

Intelligent Detection and Classification Method of Infrared Image Based on HOG Feature and SVM Classifier

为了满足人工智能在目标识别方法中的应用需求,需要具备对海量数据进行智能分类、识别、判读的能力。进一步挖掘了红外目标特性数据库数据,并将基于HOG+SVM的红外目标识别算法应用于红外目标识别过程中。选择采集到的汽车、直升机、飞机、舰船、无人机等目标,并结合HOG算子与SVM分类方法来实现红外目标检测与分类算法,从而实现了红外目标智能化分类研究,为后续目标特性的进一步分析以及导引头智能化算法设计提供了支撑。

In order to meet the application requirements of artificial intelligence in target recognition methods,the ability of intelligent classification,recognition and interpretation of massive data is necessary.The data in the infrared target characteristic database is further explored,and the infrared target recognition algorithm based on HOG+SVM is used in the infrared target recognition process.The collected targets such as cars,helicopters,planes,ships and unmanned aerial vehicles are selected,and the infrared target detection and classification algorithm is realized combining the HOG operator and the SVM classification method,so as to realize the intelligent infrared target classification research.It provides support for subsequent further analysis of the target characteristic and seeker intelligent algorithm design.