Abstract
The presence in natural vineyard images of savage foliage, weed, multiple leaves with overlapping, occlusion, and obstruction by objects due to the shadows, dust, insects and other adverse climatic conditions that occur in natural environment at the moment of image capturing, turns leaf segmentation a challenging task. In this paper, we propose a segmentation algorithm based on region growing using color model and threshold techniques for classification of the pixels belonging to vine leaves from vineyard color images captured in real field environment. To assess the accuracy of the proposed vine leaf segmentation algorithm, a supervised evaluation method was employed, in which a segmented image is compared against a manually-segmented one. Concerning boundary-based measures of quality, an average accuracy of 94.8% over a 140 image dataset was achieved. It proves that the proposed method gives suitable results for an ongoing research work for automatic identification and characterization of different endogenous grape varieties of the Portuguese Douro Demarcated Region.
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References
Bernardes, A.A., Rogeri, J.G., Oliveira, R.B., Marranghello, N., Pereira, A.S., Araujo, A.F., Tavares, J.M.R.S.: Identification of foliar diseases in cotton crop. In: Tavares, J., Natal Jorge, R. (eds.) Topics in Medical Image Processing and Computational Vision. Lecture Notes in Computational Vision and Biomechanics, vol. 8, pp. 67–85. Springer, Dordrecht (2013). https://doi.org/10.1007/978-94-007-0726-9_4
Gwo, C., Wei, C.: Plant identification through images: using feature extraction of key points on leaf contours. Appl. Plant Sci. 1, 11 (2013)
Harish, B., Hedge, A., Venkatesh, O., Spoorthy, D., Sushma, D.: Classification of plant leaves using morphological features and Zernike moments. In: IEEE International Conference on Advances in Computing, Communications and Informatics, pp. 827–1831 (2013)
Murali, S., Govindan, V.K.: Shadow detection and removal from a single image using LAB color space. Cybernet. Inf. Technol. 13(1), 95–103 (2013)
Mazhurin, A., Kharma, N.: An image segmentation assessment tool ISAT 1.0. In: Proceedings of the International Conference on Computer Vision Theory and Applications, vol. 1, pp. 436–443 (2013)
Pereira, C.S., Morais, R., Reis, M.J.C.S.: Recent advances in image processing techniques for automated harvesting purposes: a review. In: Proceedings of the Intelligent Systems Conference 2017, pp. 566–575 (2017)
Reis, M.J.C.S., Morais, R., Peres, E., Pereira, C., Contente, O., Soares, S., Valente, A., Baptista, J., Ferreira, P.J.S.G., Bulas-Cruz, J.: Automatic detection of bunches of grapes in environment from color images. J. Appl. Logic 10(4), 285–290 (2012)
Scharr, H., Minervini, M., French, A., Klukas, C., Kramer, D., Liu, X., Luengo, I., Pape, J., Polder, G., Vukadinovic, D., Yin, X., Tsaftaris, S.: Leaf segmentation in plant phenotyping: a collation study. Mach. Vis. Appl., 1–22 (2015)
Vibhute, A., Bagalkote, I.: Identification of grape variety plant species using image processing. Avishkar – Solapur Univ. Res. J. 3, 45–51 (2014)
Whalley, J., Shanmuganathan, S.: Applications of image processing in viticulture: a review. In: 20th International Congress on Modelling and Simulation, pp. 531–537 (2013)
Yanne, P., Zhang, J., Li, H.: Automatic grape varieties identification by computer. Bulletin de l’Organisation Internationale de la Vigne et du Vin 84, 5–14 (2011)
Acknowledgment
The Institute of Electronics and Informatics Engineering of Aveiro (IEETA) research unit is funded by National Funds through the FCT – Foundation for Science and Technology, in the context of the project UID/CEC/00127/2013.
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Pereira, C.S., Morais, R., Reis, M.J.C.S. (2018). Pixel-Based Leaf Segmentation from Natural Vineyard Images Using Color Model and Threshold Techniques. In: Campilho, A., Karray, F., ter Haar Romeny, B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science(), vol 10882. Springer, Cham. https://doi.org/10.1007/978-3-319-93000-8_12
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DOI: https://doi.org/10.1007/978-3-319-93000-8_12
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