基于KNN分类器的分层图像特征提取  

Layered image feature extraction based on local neural response

作　　者：范洪华 付应雄 罗志成 陈芬 FAN Honghua;FU Yingxiong;LUO Zhicheng;CHEN Fen(Faculty of Mathematics and Statistics,Hubei University,Wuhan 430062,China)

机构地区：[1]湖北大学数学与统计学学院,湖北武汉430062

出　　处：《湖北大学学报（自然科学版）》2019年第1期44-47,54,共5页Journal of Hubei University：Natural Science

基　　金：国家自然科学基金(11771130)资助

摘　　要：给出一种基于k最近邻分类器(KNN)的分层图像特征提取方法.该方法能有效地获得有代表性和判别性的模板集合,并以较低计算复杂度来获取更高的识别精度.In this paper,a layered image feature extraction method based on k-nearest neighbor classifier was presented.Based on this method,a set of representative and discriminative templates,and higher recognition accuracy with lower computational complexity were obtained.

关 键 词：特征提取 图像识别 k最近邻分类器(KNN) 

分 类 号：O621.1[理学—有机化学]