Abstract
Plants are fundamental for human beings, so it’s very important to catalogue and preserve all the plants species. Identifying an unknown plant species is not a simple task. The leaf analysis is one of the approach used for the plant species identification. This task can be completed also automatically by image processing techniques, able to analyse the leaf images and provide a classification based on prior information. Many methods have been proposed in literature in order to complete the whole cataloguing task, providing excellent classification results. Nevertheless, many of the proposed methods work only on images acquired in controlled lighting conditions and with uniform background. In this work we propose a mobile application for leaf analysis for the automatic identification of plant species. The application is mainly devoted to the identification and segmentation steps, resolving the main issues created by uncontrolled lighting conditions with very accurate results.
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Acknowledgements
This work was supported by the Research Program “Natura 2000”, funded by the Autonomous Region of Sardinia (Legge Regionale 7/2007) 2015–2018.
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Putzu, L., Di Ruberto, C., Fenu, G. (2016). A Mobile Application for Leaf Detection in Complex Background Using Saliency Maps. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_50
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