| You are in:Home/Publications/Tomato leaves diseases detection approach based on Support Vector Machines | |
Dr. mona abdelbaset :: Publications: |
|
| Title: | Tomato leaves diseases detection approach based on Support Vector Machines |
| Authors: | Usama Mokhtar, Mona AS Ali, Aboul Ella Hassenian, Hesham Hefny |
| Year: | 2015 |
| Keywords: | Not Available |
| Journal: | Computer Engineering Conference (ICENCO), 2015 11th International |
| Volume: | Not Available |
| Issue: | Not Available |
| Pages: | 246-250 |
| Publisher: | IEEE |
| Local/International: | International |
| Paper Link: | |
| Full paper | mona abdelbaset_First Paper.pdf |
| Supplementary materials | Not Available |
| Abstract: |
he study described in this paper consists of a method that applies gabor wavelet transform technique to extract relevant features related to image of tomato leaf in conjunction with using Support Vector Machines (SVMs) with alternate kernel functions in order to detect and identify type of disease that infects tomato plant. Initially, we collected real samples of diseased tomato leaves, next we isolated each leaf in single image, wavelet based feature technique has been employed to identify an optimal feature subset. Finally, a support ... |
