Plant leaf image disease detection based on Android
XIA Yong-quan
WANG Hui-min
ZENG Sha
Abstract：Aiming at the poor performance of agricultural intelligence development platform in open source, free charge and human-computer interaction based on Windows Mobile,under Android platform,a method of leaf image disease detection based on maximum between-cluster variance and Canny operator was pro-posed.Firstly,adaptive median filter was used to smooth leaf images.Secondly,the images were processed by grey scale transformation.Then,the transformed images were segmented to bi-value images by adopting a method based on maximum between-cluster variance.Finally,the bi-value images images were processed by edge detection based on Canny operator.Experimental result showed that this method achieved leaf image disease detection under Android platform.The method which could reduce marginal noise and extract the edge of leaf image disease effectively provided robustness,effectiveness and correctness.
Keywords：Android terminalplant leaf imagedisease detectionmaximum between-cluster varianceCan-ny operatoradaptive median filter
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 71-74 )