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Image processing approach for grading tobacco leaf based on color and quality Cover

Image processing approach for grading tobacco leaf based on color and quality

Open Access
|Dec 2019

References

  1. Bin, J., Ai, F.-F., Fan, W., Zhou, J.-H., Yun, Y.-H. and Liang, Y.-Z. 2016. A modified random forest approach to improve the multi-class classification performance of tobacco leaf grades coupled with NIR spectroscopy. RSC Advances 636: 30353–30361.
  2. Chen, Y.-R., Chao, K. and Kim, M. S. 2002. Machine vision technology for agricultural applications. Computers and Electronics in Agriculture 362–3: 173–191.
  3. Drope, J. and Schluger, N. W. (Eds), 2018. The tobacco atlas, 6th ed., American Cancer Society, Inc., GA.
  4. FAO 2018a. Tobacco, available at: www.fao.org/land-water/databases-and-software/crop-information/tobacco/en/(accessed September 6, 2018).
  5. FAO 2018b. Tobacco commodity rankings, available at: www.fao.org/faostat/en/#rankings/countries_by_commodity (accessed September 6, 2018).
  6. Jianqiang, Z., Weijuan, L., Huaihui, Z., Ying, H., Panpan, Y., Changyu, L., Yanmei, Y. and Ming, L. 2018. Automatic classification of tobacco leaves based on near-infrared spectroscopy and non-negative least squares. Journal of Near Infrared Spectroscopy 262: 101–105.
  7. Laykin, S. S., Alchanatis, V. V., Fallik, E. E. and Edan, Y. Y. 2002. Image–processing algorithms for tomato classification. Transactions of the ASAE 453: 851–859.
  8. Liu, J., Shen, J., Shen, Z. and Liu, R. 2012. Grading tobacco leaves based on image processing and generalized regression neural network. 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, pp. 89–93.
  9. Mallikarjuna, P. B. and Guru, D. S. 2013. Fusion of texture features and SBS method for classification of tobacco leaves for automatic harvesting, Springer, New Delhi, pp. 115–126.
  10. Mashithoh, E. 2013. Pengembangan Model Penentuan Kualitas Buah Berdasar Parameter Warna. Dissertation, Universitas Gadjah Mada, Yogyakarta.
  11. Ni, L.-J., Zhang, L.-G., Xie, J. and Luo, J.-Q. 2009. Pattern recognition of Chinese flue-cured tobaccos by an improved and simplified K-nearest neighbor classification algorithm on near-infrared spectra. Analytica Chimica Acta 6331: 43–50.
  12. PTPN X. 2016. Research and Development division of PTPN X Klaten. Manual Pelatihan Calon Grader. PT, Indonesia.
  13. Zhang, F. and Zhang, X. 2011. Classification and quality evaluation of tobacco leaves based on image processing and fuzzy comprehensive evaluation. Sensors 113: 2369–2384.
Language: English
Page range: 1 - 10
Submitted on: Jan 30, 2019
Published on: Dec 16, 2019
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Agus Harjoko, Adhi Prahara, Tri Wahyu Supardi, Ika Candradewi, Reza Pulungan, Sri Hartati, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.