Abstract
Some foot plant diseases such as flat foot and cave foot are usually diagnosed by a human expert. In this paper we propose an original method to diagnose these diseases by using optical color foot plant images. A number of modern image processing and pattern recognition techniques have been employed to configure a system that can dramatically decrease the time in which such analysis are performed, besides delivering robust and reliable results to complement efficiently the specialist’s task. Our results demonstrate the feasibility of building such automatic diagnosis systems that can be used as massive first screening methods for detecting foot plant pathologies.
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Mora, M., Jarur, M.C., Pavesi, L., Achu, E., Drut, H. (2007). A Pattern Recognition Approach to Diagnose Foot Plant Pathologies: From Segmentation to Classification. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science(), vol 4594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73599-1_51
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DOI: https://doi.org/10.1007/978-3-540-73599-1_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73598-4
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