河南农业科学2018，Vol.47Issue(4)：154-160,7.DOI:10.15933/j.cnki.1004-3268.2018.04.029
基于字典学习的马铃薯叶片病害图像识别算法
Identification Algorithm of Potato Diseases on Leaves Using Dictionary Learning Theory
摘要
Abstract
In this study,an algorithm was designed using compressive sensing theory to classify potato diseases for the purpose of identification and prevention of potato leaf diseases timely.Leaf image dictionaries of potato early blight,late blight and grey mold were generated using K-singular value decomposition (K-SVD) algorithm.The sparse coefficient matrix of one disease image was then decomposed by the above dictionaries respectively using orthogonal matching pursuit (OMP) and the image was reconstructed.RMSE of each reconstruction was compared and the smallest RMSE was obtained by the related disease dictionary.This method can learn image features automatically and reduce the complexity of image segmentation and feature extraction compared with the method based on support vector machine (SVM).The recognition rate for the three disease plots reached 95.33％,higher than the method based on SVM (92％).关键词
马铃薯病害/图像识别/压缩感知/字典学习/K-SVD/正交匹配追踪算法Key words
Potato diseases/Image recognition/Sparse sensing/Dictionary learning/K-SVD/OMP分类
农业科技引用本文复制引用
赵建敏,芦建文..基于字典学习的马铃薯叶片病害图像识别算法[J].河南农业科学,2018,47(4):154-160,7.基金项目
内蒙古自治区高等学校科学研究项目(NJZY144) （NJZY144）
