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

Authors:
D. S. Guru;P. B. Mallikarjuna
Affiliations:
University of Mysore, Manasagangothri, Mysore, Karnataka, India.;University of Mysore, Manasagangothri, Mysore, Karnataka, India
Venue:
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Year:
2010

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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.