Identification of rice seed varieties using neural network

被引：63

作者：

Liu Z.-Y. ^{[1
]}

Cheng F. ^{[1
]}

Ying Y.-B. ^{[1
]}

Rao X.-Q. ^{[1
]}

机构：

[1] School of Biosystems Engineering and Food Science, Zhejiang University

来源：

Journal of Zhejiang University-SCIENCE B | 2005年 / 6卷 / 11期

关键词：

Classification; Digital image processing; Machine vision; Neural network; Rice seeds;

D O I：

10.1631/jzus.2005.B1095

中图分类号：

学科分类号：

摘要：

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.

引用

页码：1095 / 1100

页数：5

共 18 条

[1]

Draper S.R., Travis A.J., Preliminary observations with a computer based system for analysis of the shape of seeds and vegetative structures, J. Nat. Inst. Agric. Botany, 16, 3, pp. 387-395, (1984)

[2]

Hawk A.L., Kaufmann H.H., Watson C.A., Reflectance characteristics of various grain, Cereal Sci. Today, 15, 11, pp. 381-384, (1970)

[3]

Huang X.Y., Li J., Jiang S., Study on identification of rice varieties using computer vision, Journal of Jiangsu University (Natural Science Edition), 25, 2, pp. 102-104, (2004)

[4]

Keefe P.D., A dedicated wheat grading system, Plant Varieties and Seeds, 5, pp. 27-33, (1992)

[5]

Lai F.S., Zayas I., Pomeranz Y., Application of pattern recognition techniques in the analysis of cereal grains, Cereal Chemistry, 63, 2, pp. 168-174, (1986)

[6]

Luo X., Jayas D.S., Symons S.J., Identification of damaged kernels in wheat using a color machine vision, Journal of Cereal Science, 30, 1, pp. 45-59, (1999)

[7]

Majumdar S., Jayas D.S., Classification of cereal grains using machine vision. IV. Combined morphology, color and texture models, Trans. ASAE, 43, 6, pp. 1689-1694, (2000)

[8]

Majumdar S., Jayas D.S., Hehn J.L., Bulley N.R., Classification of various grains using optical properties, Canadian Agric. Eng., 38, 2, pp. 139-144, (1996)

[9]

Myers D.G., Edsall K.J., The application of image processing techniques to the identification of Australian wheat varieties, Plant Var. and Seeds, 2, 2, pp. 109-116, (1989)

[10]

Neuman M., Sapirstein H.D., Shwedyk E., Bushuk W., Discrimination of wheat class and variety by digital image analysis of whole grain samples, J. Cereal Sci., 6, pp. 125-132, (1987)

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