Centroid of the image keeps affine covariance,but it can be only used to eliminate translation.In order to extract affine invariant features conveniently,it is necessary to construct centroid-like points that keep affine covariance and are different from the centroid.The existing algorithms are either computationally expensive or not suitable for binary images.In view of this,G-centroid is proposed.It was obtained by modifying the definition of centroid in the polar coordinate system,and the transformation function of integral along radial direction was introduced,thus making most of current centroid-like construction algorithms are special cases of the proposed G-centroid.Experimental results show that obtained G-centroid is more robustness to noise by introducing functions about central projection,compared with the generalized centroid,cross-weighted centroid and other methods.
关键词
特征提取/仿射协变/仿射变换参数恢复/质心/抗噪性
Key words
Feature extraction/Affine covariance/Parametric estimation of affine transformations/Centroid/Robustness to noise
维普
万方数据