仿射高斯描绘子及其在模式识别中的应用  

Affine Gaussian Descriptors and Their Application in Pattern Recognition

作　　者：刘亦书[1] 

机构地区：[1]华南师范大学地理科学学院,广州510631

出　　处：《模式识别与人工智能》2007年第6期770-775,共6页Pattern Recognition and Artificial Intelligence

基　　金：广东省自然科学基金博士启动资助项目(No.04300033)

摘　　要：在不同位置、从不同角度拍摄同一个二维景物,得到的图像几何形状是不同的,这种几何变形通常可用仿射变换来描述.因此,寻找一组关于仿射变换不变的特征是识别这类图像的关键.本文构造一组仿射不变的特征,即仿射高斯描绘子.构造过程主要是,先计算图像的协方差矩阵,再由该矩阵的特征值和特征向量生成一组同心椭圆,进而利用二维高斯函数构造出仿射高斯描绘子.将这些仿射不变量用于模式识别,以获得较高的识别率.Finding efficient features which are invariant under affine transformation is the key to recognizing the images captured at different angles. Affine invariants, such as affine Gaussian descriptors, are derived in this paper. The covariance matrix of the given image is computed at first. Then its eigenvalues and eigenvectors are calculated, by which a set of ellipses with the same center are generated. Finally, affine Gaussian descriptors are derived based on 2-dimensional Gaussian function and image compactification theory. Numerical experiments are carried out and the results show that the performance of affine Gaussian descriptors is high.

关 键 词：仿射高斯描绘子 协方差矩阵 仿射变换 特征值 特征向量 紧化 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]