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dc.contributor.authorBhatt, Upendra Mohan-
dc.date.accessioned2025-01-21T04:58:12Z-
dc.date.available2025-01-21T04:58:12Z-
dc.date.issued2017-10-
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/8068597-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16840-
dc.description.abstractPlants are to be considered as one of the important things that plays a very essential role for all living beings exists on earth. But due to some unawareness and environment deterioration, some very rare plants are on the verge of extinction. Knowledge of rare leaves used for medicine and other plants is very critical in future. Leaf identification and classification plays a vital role for plant species recognition. In recent years, most of the researchers dedicate their work on leaf characterization. Leaf shape is the major parameter to classify plants. A new approach is to extract 15 features from the leaf using Canny Edge Detector and classify 22 different kinds of plants with SVM classifier.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectImage segmentationen_US
dc.subjectSVM classifieren_US
dc.subjectCanny edge detectoren_US
dc.titleLeaf classification and identification using Canny Edge Detector and SVM classifieren_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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