分级特征提取与选择及在自动目标识别系统中的应用  

Hierarchical Feature Extraction and Selection Method and the Applications in Automatic Target Recognition System

作　　者：梅雪[1] 张继法[1] 许松松[1] 巩建鸣[2] 

机构地区：[1]南京工业大学自动化与电气工程学院,江苏南京210009 [2]南京工业大学机械与动力工程学院,江苏南京210009

出　　处：《遥感技术与应用》2012年第5期712-715,共4页Remote Sensing Technology and Application

基　　金：江苏省高校自然科学基金项目(09KJB510002);国家自然科学基金项目(60805002);江苏省博士后科研资助计划(1001027B);南京工业大学学科基金(39710006)

摘　　要：应用于遥感图像、武器制导等的自动目标识别系统中,经常遇到形状相似目标的鉴别问题。为提高其识别的快速性和识别率,提出一种分级的基于形状的目标识别方法。借鉴人类视觉感知方式提取多尺度特征,大尺度下采用全局特征快速粗分类,小尺度下采用局部特征鉴别形状相似目标。然后运用模糊规则对提取的特征进行选择,降低特征维数,加快目标匹配过程。实验结果表明:该方法能快速有效地识别形状相似的目标,特征选择后平均识别率较选择之前提高了6.9%。Similar shape object recognition is widely used in automatic target recognition system of remote sensing and weapon guidance. A hierarchical method of shape feature extraction and selection is proposed to increase the recognition efficiency and rate. I.earning from human visual perception, multi-scale features are extracted. C-lobal features are used to make a quick classification,and local features are used to distinguish targets with similar shape. To achieve the feature selection, fuzzy criterion is introduced which improves the matching processing and increases the recognition rate. Experimental results show this method is an effective and general way in recognizing targets with similar shape,and the feature selection improves the recognition rate by 6.9%than before.

关 键 词：形状识别 特征提取与选择 分级识别 小波矩 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]