CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11549 > Article
Poster + Presentation + Paper
10 October 2020 Detection of potato early blight based on hyperspectral imaging
F. Zhang, H. M. Li, X. T. Li, W. Zhuo, X. F. Yu, D. W. Wang, J. Feng
Author Affiliations +
Proceedings Volume 11549, Advanced Optical Imaging Technologies III; 115491V (2020) https://doi.org/10.1117/12.2575049
Event: SPIE/COS Photonics Asia, 2020, Online Only
Conference Poster
Abstract
Two non-destructive detection methods for potato blight based on hyperspectral imaging were used: convolutional neural network (CNN) and support vector machine (SVM) to classify potato leaves. By comparing the classification results, the advantages and disadvantages of different methods are analyzed. In the experiment, normal potato leaves and early blight leaves were selected as research objects. Hyperspectral images of samples were obtained by hyperspectral imaging system, and then principal component images were extracted by principal component analysis method. It was found that the principal component images of normal leaves and blight leaves were significantly different, and finally two models of blight detection were established for convolutional neural network and support vector machine. The experimental results showed that the convolutional neural network was better than the support vector function in the detection of potato blight.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
F. Zhang, H. M. Li, X. T. Li, W. Zhuo, X. F. Yu, D. W. Wang, and J. Feng "Detection of potato early blight based on hyperspectral imaging", Proc. SPIE 11549, Advanced Optical Imaging Technologies III, 115491V (10 October 2020); https://doi.org/10.1117/12.2575049
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 6 PAGES + POSTER + PRESENTATION
DOWNLOAD PAPER SAVE TO MY LIBRARY
DOWNLOAD
POSTER
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Hyperspectral imaging
Convolutional neural networks
Analytical research
Imaging systems
Nondestructive evaluation
Principal component analysis
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top