New Method for Scale-invariant Feature Extracting of Images
YU Wen-xian · Signal Processing · 2007
This paper presents a new seale-invariant feature extracting method using kernels.The method is an extension of the framework of finding geometric invariant features proposed by Chen et al [ 1 ].A deeper research of initial function is provided and a family of kernels invariant to scale is constructed.When used for target recognition,the error of sampling of images is considered into the Fisher like rule function,which provides an optimal chose of kernel parameters.It is shown that the new method is well suitable for classification of two classes' problem in our experiments.