XIA Yong-quan, WANG Hui-min and ZENG Sha. Plant leaf image disease detection based on Android[J]. Journal of Light Industry, 2014, 29(2): 71-74. doi: 10.3969/j.issn.2095-476X.2014.02.018
Citation:
XIA Yong-quan, WANG Hui-min and ZENG Sha. Plant leaf image disease detection based on Android[J]. Journal of Light Industry, 2014, 29(2): 71-74.
doi:
10.3969/j.issn.2095-476X.2014.02.018
Plant leaf image disease detection based on Android
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College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China
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Received Date:
2013-12-03
Available Online:
2014-03-15
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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 proposed.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.
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