Dual energy X-ray image analysis for classifying vitreousness in durum wheat

被引:23
作者
Neethirajan, S.
Jayas, D. S.
Karunakaran, C.
机构
[1] Univ Manitoba, Canadian Wheat Ctr Grain Storage Res Biosyst Engn, Winnipeg, MB R3T 5V6, Canada
[2] Canadian Light Source Inc, Saskatoon, SK S7N 0X4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
dual energy X-ray images; vitreous kernels; non-vitreous kernels; statistical classifiers; neural network classifiers;
D O I
10.1016/j.postharvbio.2007.03.009
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Dual energy X-ray imaging technique is an alternative to simple transmission X-ray imaging. The former has the ability to reveal the internal density changes of a scanned object by exploiting differences in how the scanned material interacts with X-rays at different energies. The feasibility of dual energy X-ray image analysis to classify vitreousness in durum wheat was assessed at 12, 14 and 16% moisture content (m.c.). Algorithms were developed for the logarithmic subtraction of images and for extraction of features. Histogram groups and total gray values were extracted front the dual energy subtracted images. Statistical and neural network classifiers were used for identifying vitreous and non-vitreous kernels from the sample images. Neural network classifiers correctly classified vitreous and non-vitreous kernels with 93% accuracy. The statistical classifiers provided 89% accuracy for vitreous and non-vitreous kernels. The over all classification accuracy for differentiating vitreous and non-vitreous kernels is higher using dual energy X-ray imaging than the simple transmission X-ray imaging. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:381 / 384
页数:4
相关论文
共 21 条
[1]  
AYELAW G, 2004, COMPUT ELECTRON AGR, V42, P1
[2]   Non-parametric image subtraction using grey level scattergrams [J].
Bromiley, PA ;
Thacker, NA ;
Courtney, P .
IMAGE AND VISION COMPUTING, 2002, 20 (9-10) :609-617
[3]  
*CGC, 2005, OFFICIAL GRAIN GUIDE
[4]  
Curry III T.S., 1990, Christensen's Physics of Diagnostic Radiology, Vfourth
[5]   Single kernel wheat hardness and fracture properties in relation to density and the modelling of fracture in wheat endosperm [J].
Dobraszczyk, BJ ;
Whitworth, MB ;
Vincent, JFV ;
Khan, AA .
JOURNAL OF CEREAL SCIENCE, 2002, 35 (03) :245-263
[6]   Differentiating vitreous and nonvitreous durum wheat kernels by using near-infrared spectroscopy [J].
Dowell, FE .
CEREAL CHEMISTRY, 2000, 77 (02) :155-158
[7]  
Dyson N. A., 1990, X-rays in Atomic and Nuclear Physics, V2nd ed.
[8]   Multi-layer neural networks for image analysis of agricultural products [J].
Jayas, DS ;
Paliwal, J ;
Visen, NS .
JOURNAL OF AGRICULTURAL ENGINEERING RESEARCH, 2000, 77 (02) :119-128
[9]   Identification of wheat kernels damaged by the red flour beetle using X-ray images [J].
Karunakaran, C ;
Jayas, DS ;
White, NDG .
BIOSYSTEMS ENGINEERING, 2004, 87 (03) :267-274
[10]  
Koo WWK, 2000, ANN NY ACAD SCI, V904, P383