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Neural Computing and Applications
Published in: Neural Computing and Applications 2/2019

26-06-2017 | Original Article

Plant disease leaf image segmentation based on superpixel clustering and EM algorithm

Authors: Shanwen Zhang, Zhuhong You, Xiaowei Wu

Published in: Neural Computing and Applications | Special Issue 2/2019

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Abstract

Plant disease leaf image segmentation plays an important role in the plant disease detection through leaf symptoms. A novel segmentation method of plant disease leaf image is proposed based on a hybrid clustering. The whole color leaf image is firstly divided into a number of compact and nearly uniform superpixels by superpixel clustering, which can provide useful clustering cues to guide image segmentation to accelerate the convergence speed of the expectation maximization (EM) algorithm, and then, the lesion pixels are quickly and accurately segmented from each superpixel by EM algorithm. The experimental results and the comparison results with similar approaches demonstrate that the proposed method is effective and has high practical value for plant disease detection.
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Metadata
Title
Plant disease leaf image segmentation based on superpixel clustering and EM algorithm
Authors
Shanwen Zhang
Zhuhong You
Xiaowei Wu
Publication date
26-06-2017
Publisher
Springer London
Published in
Neural Computing and Applications / Issue Special Issue 2/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-3067-8

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