Image Kernel for Recognition

摘要：

Kernel-based methods have been widely used in pattern recognition.But traditional kernel functions can only process 1D vectors,while image data are often 2D matrices.This paper presents a new kernel function based on RBF kernel function for image target recognition.This new kernel function can directly accept 2D image data as input data,and analyze the structural information of the targets in the images,which are often ignored by other kernel functions.This kernel function can also process target images which are obtained under different luminance conditions without any preprocessing.The experiments on UCI datasets and ALOI datasets show that,the classifier based on our kernel function can have higher classification accuracy.Because the features are not necessary in our method,the results also demonstrate a new framework of image target recognition.

作者: Zhu XiaoKai Li Xiang

作者单位: Research Institute of Space Electronics Information Technology,College of Electric Science and Engineering,NUDT,ChangSha 410073,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）