安徽大学学报（自然科学版）2013，Vol.37Issue(4)：61-67,7.DOI:10.3969/j.issn.1000-2162.2013.04.011
基于WLLE和SVM的植物叶片图像识别方法
Recognition method of plant leaves based on WLLE and SVM
摘要
Abstract
In general,noise could influence the algorithm of LLE,and nearest neighbor classifier couldn' t recognize plant leaf images effectively,a recognition method of plant leaves based on weighted locally linear embedding and support vector machine was proposed.The features of the preprocessing plant leaf images with noise were extracted by use of WLLE,and leaf feature sets were trained and recognized by the classification methods of SVM,at last,plant leaf images from the real plant leaf image database were used to take classification experiment.Experimental results showed that the proposed method improved the classification accuracy of plant leaf images.关键词
流形学习/局部线性嵌入/加权局部线性嵌入/特征提取/支持向量机/植物叶片识别Key words
manifold learning/ locally linear embedding/ weighted locally linear embedding/ feature extraction/ support vector machine/ plant leaf recognition分类
信息技术与安全科学引用本文复制引用
丁娇,梁栋,阎庆..基于WLLE和SVM的植物叶片图像识别方法[J].安徽大学学报（自然科学版）,2013,37(4):61-67,7.基金项目
国家自然科学基金资助项目(61172127) （61172127）
高等学校博士学科点专项科研基金资助项目(20113401110006) （20113401110006）
安徽省自然科学基金资助项目(1208085QF104) （1208085QF104）
安徽省高校优秀青年人才基金资助项目(2012SQRL017ZD) （2012SQRL017ZD）
