摘要
提出一种基于多特征融合和极坐标变换的目标识别方法。利用多特征融合方法,从原始图像中提取待识别目标实现维数压缩任务;引入极坐标变换和快速傅里叶变换相结合的方法,确定变换后的不变特征矩阵;通过计算不变特征矩阵和模板特征矩阵的相关性对目标进行分类识别。实验结果证明,该目标识别方法有较好的可靠性和较高的识别正确率。
This paper puts forward a method of target recognition based on multi-feature integration and polar coordinates transformation.It uses multi-feature fusion method to extract from the original image to be identified to achieve the objective dimension of compression tasks.The polar coordinate and Fast Fourier Transform（FFT） method are introduced to determine the invariant features of the transformed matrix.The targets are classified and recognized by calculating the same correlation of the characteristic matrix and the template features matrix.Experimental results show that this method has good reliability and high recognition rate.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第11期197-199,共3页
Computer Engineering
关键词
目标识别
特征融合
极坐标
快速傅里叶变换
target recognition
feature fusion
polar coordinate
Fast Fourier Transform（FFT）
