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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Baltazar A, Aranda JI, Aguilar GG (2008) Bayesian classification of ripening stages of to-mato fruit using acoustic impact and colorimeter sensor data. Comput Electron Agric 60(2):113–121
Furfaro R, Ganapol BD, Johnson LF, Herwitz SR (2007) Neural network algorithm for coffee ripeness evaluation using airborne images. Appl Eng Agric 23(3):379–387
Gao H, Cai J, Liu X (2009) Automatic grading of the post-harvest fruit: a review. In: Third IFIP international conference on computer and computing technologies in agriculture. Springer, Beijing, pp 141–146
Guru DS, Mallikarjuna PB (2010) Spots and color based ripeness evaluation of tobacco leaves for automatic harvesting. In: First international conference on intelligent interactive technologies and multimedia. ACM, IIIT Allahabad., India, pp 198–202
Jabro JD, Stevens WB, Evans RG, Iversen WM (2010) Spatial variability and correlation of selected soil in the AP horizon of a CRP grassland. Appl Eng Agric 26(3):419–428
Johnson LF, Herwitz SR, Lobitz BM, Dunagan SE (2004) Feasibility of monitoring coffee field ripeness with airborne multispectral imagery. Appl Eng Agric 20(6):845–849
Lee DJ, Chang Y, Archibald JK, Greco CJ (2008a) Color quantization and image analysis for automated fruit quality evaluation. In: IEEE international conference on automation science and engineering. IEEE, Trieste, Italy, pp 194–199
Lee DJ, Chang Y, Archibald JK, Greco CJ (2008b) Robust color space conversion and color distribution analysis techniques for date maturity evaluation. J Food Eng 88:364–372
Lee D, Archibald JK, Xiong G (2011) Rapid color grading for fruit quality evaluation using direct color mapping. IEEE Trans Autom Sci Eng 8:292–302
Manickavasagam A, Gunasekaran JJ, Doraisamy P (2007) Trends in Indian flue cured virgina tobacco (Nictoina tobaccum) processing: harvesting, curing and grading. Res J Agric Biol Sci 3(6):676–681
Patricio DI, Riederb R (2018) Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review. Comput Electron Agric 153:69–81
Viscarra RA, Minasny B, Roudier P, McBratney AB (2006) Colour space models for soil science. Geoderma 133:320–337
Xu L (2008) Strawberry maturity neural network detecting system based on genetic algorithm. In: Second IFIP international conference on computer and computing technologies in agriculture, Beijing, China, pp 1201–1208
Yin H, Chai Y, Yang SX, Mitta GS (2009) Ripe tomato extraction for a harvesting robotic system. In: IEEE international conference on systems, man and cybernetics. IEEE, San Antonio, USA, pp 2984–2989
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-981-16-1681-5_13
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-1680-8
Online ISBN: 978-981-16-1681-5
eBook Packages: Computer ScienceComputer Science (R0)