Identification of rice seed varieties using neural network / 浙江大学学报(英文版)(B辑:生物医学和生物技术)
Journal of Zhejiang University. Science. B
;
(12): 1095-1100, 2005.
Article
in English
| WPRIM
| ID: wpr-263255
ABSTRACT
A digital image analysis algorithm based color and morphological features was developed to identify the six varieties (ey7954, syz3, xs11, xy5968, xy9308, z903) rice seeds which are widely planted in Zhejiang Province. Seven color and fourteen morphological features were used for discriminant analysis. Two hundred and forty kernels used as the training data set and sixty kernels as the test data set in the neural network used to identify rice seed varieties. When the model was tested on the test data set, the identification accuracies were 90.00%, 88.00%, 95.00%, 82.00%, 74.00%, 80.00% for ey7954, syz3, xs11, xy5968, xy9308, z903 respectively.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Oryza
/
Seeds
/
Species Specificity
/
Algorithms
/
Pattern Recognition, Automated
/
Artificial Intelligence
/
Image Interpretation, Computer-Assisted
/
Image Enhancement
/
Photography
/
Cluster Analysis
Type of study:
Diagnostic study
/
Prognostic study
Language:
English
Journal:
Journal of Zhejiang University. Science. B
Year:
2005
Type:
Article
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