Overbeek, Marlinda Vasty and Kaesmetan, Yampi R. and Tobing, Fenina Adline Twince (2019) Identification of Maize Leaf Diseases Cause by Fungus with Digital Image Processing (Case Study: Bismarak Village Kupang District - East Nusa Tenggara). In: 2019 5th International Conference on New Media Studies (CONMEDIA), 9-11 Oct. 2019, Bali.
Full text not available from this repository.Abstract
Characteristics in common disease caused by a fungus often makes farmers wrong in giving treatment. Prevention is given too often wrong because it is by direct observation. Therefore in this study, we propose a system to detect disease in maize leaf caused by fungi with a view of segmentation or the shape of the maize leaf-based on digital image processing. The sobel operator we used as a shape features extraction. As for the detection technique, we used multiclass Support Vector Machine algorithm with Radial Basis Function kernel. The results of the identification accuracy of the system are 92 225%.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Keywords: | Diseases , Image edge detection , Feature extraction , Kernel , Support vector machines , Fungi , Shape |
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 004 Computer Science, Data Processing, Hardware |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 15 Oct 2021 03:20 |
| Last Modified: | 15 Oct 2021 03:20 |
| URI: | https://kc.umn.ac.id/id/eprint/18791 |
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