基于香蕉雷达回波图像的特征提取与识别  

Feature extraction and recognition based on banana-radar echo images

作　　者：孟红飞[1] 牛建强[1] 杨瑞瑞[1] 段世忠[2] 

机构地区：[1]河南科技大学电子信息工程学院,河南洛阳471003 [2]中国空空导弹研究院,河南洛阳471003

出　　处：《计算机应用》2011年第2期413-415,共3页journal of Computer Applications

基　　金：河南省交通运输厅科技项目(2009P217)

摘　　要：为了解决高速公路绿色通道验货部门存在的难以用人工的方法去判断车中是否夹带违禁物的实际问题,在采集香蕉的雷达回波图像的基础上,利用灰度共生矩阵的特征提取,提出了基于反向传播(BP)神经网络对香蕉的雷达回波图像进行识别和分类的方法,编制了香蕉的雷达回波图像的识别和分类软件。通过在河南高速服务区绿色通道验货部门的实际应用,表明该软件有较好的识别和分类效果。It is difficult for the high-way green channel inspection department to detect prohibited goods in the vehicle by artificial methods.In order to solve this problem,this paper put forward a discernment and classification method based on Back-Propagation（BP） neural network,making use of gray level co-occurrence matrix to extract feature from collected radar echo image with banana.Furthermore,the software for discernment and classification of radar echo image with banana was programmed.Practical application in the high-way green channel inspection department in Henan province shows that the software has good discernment and classification performance.

关 键 词：雷达回波 特征提取 灰度共生矩阵 反向传播算法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]