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Spots and color based ripeness evaluation of tobacco leaves for automatic harvesting

Authors:

D. S. Guru,

P. B. MallikarjunaAuthors Info & Claims

IITM '10: Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia

Pages 198 - 202

https://doi.org/10.1145/1963564.1963597

Published: 27 December 2010 Publication History

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Abstract

In this paper, we propose a model based on ripeness evaluation for classification of tobacco leaves useful for automatic harvesting in a complex agriculture environment. The CIELAB color space model is used to segment the leaf from the background. We propose a spot detection algorithm to estimate density of maturity spots on a leaf using Laplacian filter and Sobel edge detector. We have computed degree of ripeness of leaf by density of mature spots on a leaf and greenness of leaf. Then, leaves are classified into three classes viz., ripe, unripe, and over-ripe based on computed degree of ripeness. Experimentation is conducted on our own dataset consisting of 274 images of tobacco leaves captured in both sunny and cloudy lighting conditions in a real tobacco field. The experimental results indicate that proposed model achieves a good average classification accuracy.

References

[1]

Lee, D., Archibald, J. K., Chang Y., and Greco, C. R. 2008. Robust color space conversion and color distribution analysis techniques for date maturity evaluation. Journal of Food Engineering, vol. 88, pp. 364--372.

Crossref

Google Scholar

[2]

Gao, H., Cai, J., and Liu, X. 2010. Automatic Grading of the Post-Harvest Fruit: A Review. Computer and Computing Technologies in Agriculture III, vol. 371, pp. 141--146.

Crossref

Google Scholar

[3]

Lee, D. J., Chang, Y., Archibald, J. K., and Greco, C. G. 2008. Color quantization and image analysis for automated fruit quality evaluation. IEEE International Conference on Automation Science and Engineering, pp. 194--199.

Google Scholar

[4]

Xu, L. 2009. Strawberry Maturity Neural Network Detecting System Based on Genetic Algorithm. Computer and Computing Technologies in Agriculture II, vol. 2, pp. 1201--1208.

Google Scholar

[5]

Furfaro, R., Ganapol, B. D., Johnson, L. F., and Herwitz, S. R. 2007. Neural Network Algorithm for Coffee Ripeness Evaluation Using Airborne Images. Applied Engineering in Agriculture, vol. 23(3), pp. 379--387.

Crossref

Google Scholar

[6]

Johnson, L. F., Herwitz, S. R., Lobitz, B. M., and Dunagan, S. E. 2004. Feasibility of Monitoring Coffee Field Ripeness with Airborne Multispectral imagery. Applied Engineering in Agriculture, vol. 20(6), pp. 845--849.

Crossref

Google Scholar

[7]

Baltazar, A., Aranda, J. I., Gonjalez, G., and Aguilar. 2008. Bayesian classification of ripening stages of tomato fruit using acoustic impact and colorimeter sensor data. Computers and Electronics in Agriculture, vol. 60, pp. 113--121.

Digital Library

Google Scholar

[8]

Zhang, J., Sokhansanj, S., Wu, S., Fang, R., Yang, W., and Winter, P. 1997. A trainable grading system for tobacco leaves. Computers and Electronics in Agriculture, vol. 16(3), pp. 231--244.

Crossref

Google Scholar

[9]

Zhang, J., Sokhansanj, S., Wu, S., Fang, R., Yang, W., and Winter, P. 1998. A transformation technique from RGB signals to the Munsell system for color analysis of tobacco leaves. Computers and Electronics in agriculture, vol. 19, pp. 155--166.

Google Scholar

[10]

Zhang, H., Han, L., and Wang, Z. 2003. A Fuzzy Classification System and Its Application. Intenational Conference on Machine learning and cybernetics, pp. 2--5.

Google Scholar

[11]

Huabo, L., Liyuan, H., and Tao, L. 2009. The Barrel Theory Based Decision-making Algorithm and Its Application. International conference on Computional Intelligence and Natural computing, vol. 1, pp. 11--14.

Digital Library

Google Scholar

[12]

Ni L., L., Zhang, L., Xie, J., and Luo, J. 2008. Pattern recognition of Chinese flue-cured tobaccos by an improved and simplified K-nearest neighbors classification algorithm on near infrared spectra. Analytica Chimica Acta, vol. 633.

Google Scholar

[13]

Viscarra, R. A., Minasny, B., Roudier, P., and A. B. McBratney, A. B. 2006. Colour space models for soil science. Geoderma, 2006. vol. 133, pp. 320--337.

Google Scholar

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Zhang YZhu YLiu XLu YLiu CZhou XFan W(2023)In-Field Tobacco Leaf Maturity Detection with an Enhanced MobileNetV1: Incorporating a Feature Pyramid Network and Attention MechanismSensors10.3390/s2313596423:13(5964)Online publication date: 27-Jun-2023
https://doi.org/10.3390/s23135964
Mallikarjuna PGuru DShadaksharaiah C(2021)Ripeness Evaluation of Tobacco Leaves for Automatic Harvesting: An Approach Based on Combination of Filters and Color ModelsData Science10.1007/978-981-16-1681-5_13(197-213)Online publication date: 20-Aug-2021
https://doi.org/10.1007/978-981-16-1681-5_13

Index Terms

Spots and color based ripeness evaluation of tobacco leaves for automatic harvesting
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation
        Video segmentation
      2. Computer vision tasks
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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Published In

IITM '10: Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia

December 2010

355 pages

ISBN:9781450304085

DOI:10.1145/1963564

Editors:
M. D. Tiwari
IIIT Allahabad, India
,
R. C. Tripathi
IIIT Allahabad, India
,
Anupam Agrawal
IIIT Allahabad, India

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 27 December 2010

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IITM '10: First International Conference on Intelligent Interactive Technologies and Multimedia

December 27 - 30, 2010

Allahabad, India

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Zhang YZhu YLiu XLu YLiu CZhou XFan W(2023)In-Field Tobacco Leaf Maturity Detection with an Enhanced MobileNetV1: Incorporating a Feature Pyramid Network and Attention MechanismSensors10.3390/s2313596423:13(5964)Online publication date: 27-Jun-2023
https://doi.org/10.3390/s23135964
Mallikarjuna PGuru DShadaksharaiah C(2021)Ripeness Evaluation of Tobacco Leaves for Automatic Harvesting: An Approach Based on Combination of Filters and Color ModelsData Science10.1007/978-981-16-1681-5_13(197-213)Online publication date: 20-Aug-2021
https://doi.org/10.1007/978-981-16-1681-5_13

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Digital mapping of coffee ripeness using UAV-based multispectral imagery

Evaluation of the Reliability of Classifiers for the Mapping of Mangrove Forest Using Landsat TM Images

Strawberry ripeness classification method in facility environment based on red color ratio of fruit rind

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Digital mapping of coffee ripeness using UAV-based multispectral imagery

Evaluation of the Reliability of Classifiers for the Mapping of Mangrove Forest Using Landsat TM Images

Strawberry ripeness classification method in facility environment based on red color ratio of fruit rind

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