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The Imaging Science Journal Volume 63, 2015 - Issue 8
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Research Article

Kernel-like impurity detection according to colour band spectral image using GA/SVM

F. ChenCollege of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, No. 1, 2nd Street, Xiasha, Hangzhou310018, China
,
P. ChenDepartment of Economic Management, Cancer Affiliated Hospital of Xinjiang Medical University, No. 789 Suzhou East Road, Urumqi830011, China
,
D. LiCollege of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, No. 1, 2nd Street, Xiasha, Hangzhou310018, China
&
F. ChengCollege of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou310058, ChinaCorrespondence[email protected]
[email protected]
Pages 469-475 | Received 25 Sep 2014, Accepted 26 May 2015, Published online: 11 Jun 2015

References

  • Zayas, I., Pomeranz, Y. and Lai, F. S. Discrimination between Arthur and Arkan wheats by image-analysis. Cereal Chem., 1985, 62/6, 478–480.
  • Keefe, P. D. and Draper, S. R. The measurement of new characters for cultivar identification in wheat using machine vision. Seed Sci. Technol., 1986, 14/3, 715–724.
  • Zayas, I., Lai, F. S. and Pomeranz, Y. Discrimination between wheat classes and varieties by image-analysis. Cereal Chem., 1986, 63/1, 52–56.
  • Maghirang, E. B., Dowell, F. E., Baker, J. E. and Throne, J. E. Automated detection of single wheat kernels containing live or dead insects using near-infrared reflectance spectroscopy. Trans. Asabe, 2003, 46/4, 1277–1282.
  • Pacheco, A. D., Aguilar, C. H., Orea, A. C., Briseno-Tepepa, B. R., Sinencio, F. S., et al. Evaluation of wheat and maize seeds by photoacoustic microscopy. Int. J. Thermophys., 2009, 30/6, 2036–2043. doi: 10.1007/s10765-009-0674-3
  • Choudhary, R., Paliwal, J. and Jayas, D. S. Classification of cereal grains using wavelet, morphological, colour, and textural features of non-touching kernel images. Biosys. Eng., 2008, 99/3, 330–337. doi: 10.1016/j.biosystemseng.2007.11.013
  • Delwiche, S. R. and Kim, M. S. Hyperspectral imaging for detection of scab in wheat. Proc. SPIE, 2000, 4203, 13. doi: 10.1117/12.411752
  • Jayas, D. S., Singh, C. B., Paliwal, J. and White, N. D. G. Identification of insect-damaged wheat kernels using short-wave near-infrared hyperspectral and digital colour imaging. Comput. Electron. Agr., 2010, 73/2, 118–125. doi: 10.1016/j.compag.2010.06.001
  • Neethirajan, S., Karunakaran, C., Symons, S. and Jayas, D. S. Classification of vitreousness in durum wheat using soft X-rays and transmitted light images. Comput. Electron. Agr., 2006, 53/1, 71–78. doi: 10.1016/j.compag.2006.03.001
  • Davies, E. R. The application of machine vision to food and agriculture: a review. Imaging Sci. J., 2009, 57, 197–217. doi: 10.1179/174313109X454756
  • Goldberg, D. E. Genetic algorithms in search, optimization and machine learning, 1989 (Addison-Wesley, New York)
  • Viana, M., Querol, X., Alastuey, A., et al. Identification of PM sources by principal component analysis (PCA) coupled with wind direction data. Chemosphere, 2006, 65/11, 2411–2418. doi: 10.1016/j.chemosphere.2006.04.060
  • Hsu, C. W., Chang, C. C. and Lin, C. J. A practical guide to support vector classification, 2003 (Computer and Science Engineering, National Taiwan University, Taipei)
  • Chen, F. N. and Cheng, F. Defective kernel detection using a linear colour CCD. Imaging Sci. J., 2013, 61, 361–368. doi: 10.1179/1743131X11Y.0000000052
  • Peng, S. H., Xu, Q. H., Ling, X. B., Peng, X. N., Du, W., et al. Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines. FEBS Lett., 2003, 555/2, 358–362. doi: 10.1016/S0014-5793(03)01275-4
  • Manickavasagan, A., Sathya, G. and Jayas, D. S. Comparison of illuminations to identify wheat classes using monochrome images. Comput. Electron. Agr., 2008, 63/2, 237–244. doi: 10.1016/j.compag.2008.03.002
  • Tahir, A., Neethirajan, S., Jayas, D., Shahin, M., Symons, S., et al. Evaluation of the effect of moisture content on cereal grains by digital image analysis. Food Res. Int., 2007, 40/9, 1140–1145. doi: 10.1016/j.foodres.2007.06.009

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