Ahmad Fakhri, Ab. Nasir and M Nordin, A Rahman and Nashriyah, Mat and Abd Rasid, Mamat and Ahmad Shahrizan, Abdul Ghani (2018) Image pre-processing algorithm for Ficus deltoidea Jack (Moraceae) varietal recognition: a repeated perpendicular line scanning approach. International Journal of Engineering & Technology, 7 (2). pp. 49-53. ISSN 2227-524X. (Published)
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Image pre-processing algorithm for Ficus deltoidea Jack (Moraceae) varietal recognition. A repeated perpendicular line scanning approach.pdf Download (504kB) | Preview |
Abstract
Image pre-processing task is always the first crucial step in plant species recognition system which is responsible to keep precision of feature measurement process. Some of researchers have developed the image pre-processing algorithm to remove petiole section. However, the algorithm was developed using semi-automatic algorithm which is strongly believed to give an inaccurate feature measurement. In this paper, a new technique of automatic petiole section removal is proposed based on repeated perpendicular petiole length scanning concept. Four phases of petiole removal technique involved are: i) binary image enhancement, ii) boundary binary image contour tracing, iii) petiole section scanning, and iv) optimal image size retaining and cropping. The experiments are conducted using six varieties of Ficus deltoidea Jack (Moraceae) leaves. The experimental results indicate that the segmentation results are acceptably good since the digital leaf images have less than 1% of segmentation errors on several ground truth images.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Ficus deltoidea Jack; Image pre-processing; Image processing; Leaf recognition; Plant species recognition |
| Subjects: | T Technology > TS Manufactures |
| Faculty/Division: | Faculty of Manufacturing Engineering |
| Depositing User: | Dr. Ahmad Fakhri Ab. Nasir |
| Date Deposited: | 11 Dec 2018 03:46 |
| Last Modified: | 11 Dec 2018 03:46 |
| URI: | http://umpir.ump.edu.my/id/eprint/22641 |
| Download Statistic: | View Download Statistics |
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