Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/43951
| Title: | Automatic Identification of Botanical Samples of leaves using Computer Vision | Authors: | Yadav, Anjali Dutta, Malay Kishore Travieso, Carlos M. Alonso, Jesus B. |
UNESCO Clasification: | 3307 Tecnología electrónica | Keywords: | Support vector machines , Feature extraction , Image segmentation , Classification algorithms , Shape , Gray-scale, Image Processing , Features extraction , GLCM features , Classification , Multi-SVM | Issue Date: | 2017 | Journal: | 2017 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2017 - Proceedings | Conference: | 5th IEEE International Work Conference on Bio-Inspired Intelligence, IWOBI 2017 | Abstract: | Leaf can be one of the many different parameters on the basis of which a plant can be uniquely identified. Many plants types are on the verge of extinction and can be taken care of, if identified correctly. The proposed method discusses an automated image processing system for leaf classification. The leaf pixels from the image are segmented and termed as region of interest (ROI). A set of geometrical, textural and statistical features is extracted for each input sample and analyzed using a multi class SVM classifier. The proposed system has achieved an accuracy of 97% with a sensitivity of 98.32%. The results are encouraging for a dataset consisting of 10 different leaf classes and can be used for development of some real time application. | URI: | http://hdl.handle.net/10553/43951 | ISBN: | 9781538608500 | DOI: | 10.1109/IWOBI.2017.7985531 | Source: | 2017 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2017 - Proceedings (7985531) |
| Appears in Collections: | Actas de congresos |
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.