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Sensors 2016, 16(5), 676; doi:10.3390/s16050676

Spectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves

College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
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Author to whom correspondence should be addressed.
Academic Editor: Simon X. Yang
Received: 20 February 2016 / Revised: 30 April 2016 / Accepted: 5 May 2016 / Published: 11 May 2016
(This article belongs to the Special Issue Sensors for Agriculture)
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Abstract

This study investigated both spectrum and texture features for detecting early blight disease on eggplant leaves. Hyperspectral images for healthy and diseased samples were acquired covering the wavelengths from 380 to 1023 nm. Four gray images were identified according to the effective wavelengths (408, 535, 624 and 703 nm). Hyperspectral images were then converted into RGB, HSV and HLS images. Finally, eight texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) based on gray level co-occurrence matrix (GLCM) were extracted from gray images, RGB, HSV and HLS images, respectively. The dependent variables for healthy and diseased samples were set as 0 and 1. K-Nearest Neighbor (KNN) and AdaBoost classification models were established for detecting healthy and infected samples. All models obtained good results with the classification rates (CRs) over 88.46% in the testing sets. The results demonstrated that spectrum and texture features were effective for early blight disease detection on eggplant leaves. View Full-Text
Keywords: texture feature; hyperspectral imaging; RGB/HSV/HLS image; classification; early blight disease; eggplant texture feature; hyperspectral imaging; RGB/HSV/HLS image; classification; early blight disease; eggplant
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Xie, C.; He, Y. Spectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves. Sensors 2016, 16, 676.

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