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Advanced Plant Leaf Classification Through Image Enhancement and Canny Edge Detection

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dc.contributor.author Thanikkal, Jibi G
dc.contributor.author Dubey, Ashwani Kumar
dc.contributor.author Thomas, MT
dc.date.accessioned 2022-03-03T04:30:30Z
dc.date.available 2022-03-03T04:30:30Z
dc.date.issued 2018
dc.identifier.citation J. G. Thanikkal, A. K. Dubey and M. T. Thomas, "Advanced Plant Leaf Classification Through Image Enhancement and Canny Edge Detection," 2018 7th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2018, pp. 1-5 en_US
dc.identifier.other 10.1109/ICRITO.2018.8748587
dc.identifier.uri http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/172
dc.description.abstract Accuracy in identification of any plant is achieved by understanding and extracting the plant features. Image processing techniques has gained interest in identifying the plants in realist and accurate manner. Among them, Edge detection techniques has very important role in creation of database for plant identification. Edge filtering and optimization technique to create continuous edges makes Canny edge detection widely popular to retrieve image characteristics. The proposed contour based image segmentation process filter morphological features from plant leaves. Detailed vein and texture extraction of plant leave using Canny edge detector are explained. en_US
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.subject Plants en_US
dc.subject Image processing en_US
dc.subject Canny edge detection en_US
dc.subject Morphological features en_US
dc.title Advanced Plant Leaf Classification Through Image Enhancement and Canny Edge Detection en_US
dc.type Article en_US


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