Support vector machine for recognition of cucumber leaf diseases

Support vector machine (SVM) is discussed to use for recognizing cucumber leaf diseases in this paper. Considering that it is a small number of samples, a new experimental program has been proposed which takes each spot of leaves as a sample instead of taking each leaf as a sample. In the experiment...

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Bibliographic Details
Published in:2010 2nd International Conference on Advanced Computer Control Vol. 5; pp. 264 - 266
Main Authors: Zhang Jian, Zhang Wei
Format: Conference Proceeding
Language:English
Japanese
Published: IEEE 2010
Subjects:
Algorithm design and analysis
classification
Crops
cucumber leaf disease
Diseases
Functional analysis
Image recognition
Kernel
kernel function
Machine intelligence
pattern recognition
Risk analysis
support vector machine
Support vector machine classification
Support vector machines
ISBN:1424458455, 9781424458455
Online Access:Get full text
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Summary:Support vector machine (SVM) is discussed to use for recognizing cucumber leaf diseases in this paper. Considering that it is a small number of samples, a new experimental program has been proposed which takes each spot of leaves as a sample instead of taking each leaf as a sample. In the experiments Radial Basis Function (RBF), polynomial and Sigmoid kernel function were also used to carry out comparative tests. The results showed that, the SVM method based on RBF kernel function and taking each spot as a sample made the best performance for classification of cucumber leaf diseases.
ISBN:1424458455
9781424458455
DOI:10.1109/ICACC.2010.5487242