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

Author:

Harjoko Agus,Prahara Adhi,Supardi Tri Wahyu,Candradewi Ika,Pulungan Reza,Hartati Sri

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Reference13 articles.

1. A modified random forest approach to improve the multi-class classification performance of tobacco leaf grades coupled with NIR spectroscopy;RSC Advances,2016

2. Machine vision technology for agricultural applications;Computers and Electronics in Agriculture,2002

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).

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