Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2099
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dc.contributor.authorJayalath, A. D. A. D. S-
dc.contributor.authorAmarawanshaline, T. G. A. G. D-
dc.contributor.authorNawinna, D. P-
dc.contributor.authorNadeeshan, P. V. D-
dc.contributor.authorJayasuriya, H. P-
dc.date.accessioned2022-04-29T05:56:38Z-
dc.date.available2022-04-29T05:56:38Z-
dc.date.issued2019-12-18-
dc.identifier.citationA. D. A. D. S. Jayalath, T. G. A. G. D. Amarawanshaline, D. P. Nawinna, P. V. D. Nadeeshan and H. P. Jayasuriya, "Identification of Medicinal Plants by Visual Characteristics of Leaves and Flowers," 2019 14th Conference on Industrial and Information Systems (ICIIS), 2019, pp. 125-129, doi: 10.1109/ICIIS47346.2019.9063275.en_US
dc.identifier.issn2164-7011-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2099-
dc.description.abstractIn Ayurveda medicine, correct identification of medicinal plants is of great importance. Plants are identified by human experts using their visual features and aroma. Incorrect identification of medicinal plants may lead to adverse results. Plant identification can be automated using visual morphological characteristics such as the shape, color, and texture of the leaves and flowers. This paper presents how rare medicinal plants were identified with high accuracy by applying image processing and machine learning capabilities. For this study, a database was created from scanned images of leaves and flowers of rare medicinal plants used in Sri Lankan Ayurveda medicine. Both the front and back sides of leaves and flowers were captured. The leaves are classified based on the unique feature combination. Identification rates up to 98% have been obtained when tested over 10 plants.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2019 14th Conference on Industrial and Information Systems (ICIIS);Pages 125-129-
dc.subjectIdentificationen_US
dc.subjectMedicinal Plantsen_US
dc.subjectVisual Characteristicsen_US
dc.subjectLeavesen_US
dc.subjectFlowersen_US
dc.titleIdentification of Medicinal Plants by Visual Characteristics of Leaves and Flowersen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICIIS47346.2019.9063275en_US
Appears in Collections:Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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