Abstract
In this paper, a novel filter-based model for classification of tobacco leaves for the purpose of harvesting is proposed. The filter-based model relies on estimation of degree of ripeness of a leaf using combination of filters and color models. Degree of ripeness of a leaf is computed using density of maturity spots on a leaf surface and yellowness of a leaf. A new maturity spot detection algorithm based on combination of first order edge extractor (sobel edge detector or canny edge detector) and second order high-pass filtering (Laplacian filter) is proposed to compute the density of maturity spots on a unit area of a leaf. Further, a simple thresholding classifier is designed for the purpose of classification. Superiorities of the proposed model in terms of effectiveness and robustness are established empirically through extensive experiments.
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Mallikarjuna, P.B., Guru, D.S., Shadaksharaiah, C. (2021). Ripeness Evaluation of Tobacco Leaves for Automatic Harvesting: An Approach Based on Combination of Filters and Color Models. In: Verma, G.K., Soni, B., Bourennane, S., Ramos, A.C.B. (eds) Data Science. Transactions on Computer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-16-1681-5_13
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DOI: https://doi.org/10.1007/978-981-16-1681-5_13
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