Abstract
In an agricultural country like India, majority of population depend on plant produce for their survival. Plants occupy a large portion of our ecosystem. In order to derive different benefits from plants in an optimum manner, one needs to be aware of the properties being possessed by plants. For that purpose, one needs to have proper source carrying significant information about plants and an expert so as to respond to ones queries. However, both these are not available in adequate which drives the need to create automation in the process of recognition of leaves for plant classification. Thus, a novel algorithm has been developed which helps in recognizing different varieties of leaves without human interference. The system uses real time images of leaves and extracts physiological as well as morphological features of the leaves, which are then fed as input to a classifier. The same has been implemented on a Back propagation based neural network classifier and a comparative study has been made. The study shows that the recognition rates of the proposed method are more accurate than that of BPNN and the proposed algorithm is found to be an efficient one.
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Mohanty, P., Pradhan, A.K., Behera, S., Pasayat, A.K. (2015). A Real Time Fast Non-soft Computing Approach towards Leaf Identification. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_92
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DOI: https://doi.org/10.1007/978-3-319-11933-5_92
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11932-8
Online ISBN: 978-3-319-11933-5
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