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 |