Chowdhury, Pinaki Nath and Shivakumara, Palaiahnakote and Nandanwar, Lokesh and Samiron, Faizal and Pal, Umapada and Lu, Tong (2022) Oil palm tree counting in drone images. Pattern Recognition Letters, 153. pp. 1-9. ISSN 0167-8655, DOI https://doi.org/10.1016/j.patrec.2021.11.016.
Full text not available from this repository.Abstract
When the images are captured by drones, the effect of oblique angles, distance variations and open en-vironment are the main challenges for successful palm tree detection. This paper presents a method to-wards palm tree counting in Drone images using a novel idea of detecting dominant points by exploring Generalized Gradient Vector Flow, which defines symmetry based on gradient direction of the pixels. For each dominant point, we use angle information for classifying diagonal dominant points. It is intuition that the direction of the branches of tree converges at center of tree irrespective of the type of tree and plants. This observation motivated us to expand the direction of diagonal dominant points until it finds intersection point with another diagonal dominant point and this results in candidate points. For each candidate point, the proposed method constructs the ring by considering the distance between the in-tersection point and nearest neighbor candidate point as radius. This outputs region of interest and it includes center of each tree in the image. To ease the effect of complex background, we explore YOLOv5 architecture to remove false region of interests. This step results in counting oil palm trees in the mages irrespective of tree type of palm family. Experimental results on our dataset of the images captured by drones and standard dataset of coconut images captured by unmanned aerial vehicle of different trees show that the proposed method is effective and performs better than SOTA methods. (c) 2021 Published by Elsevier B.V.
| Item Type: | Article |
|---|---|
| Funders: | Universiti Malaya[GPF014D-2019], National Natural Science Foundation of China (NSFC)[61672273], National Natural Science Foundation of China (NSFC)[61832008], National Natural Science Foundation of China (NSFC)[BK20160021], National Science Fund for Distinguished Young Scholars. |
| Uncontrolled Keywords: | Oil palm tree detection;Drone images;Generalized gradient vector flow;Angle analysis |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 27 Jul 2022 03:03 |
| Last Modified: | 27 Jul 2022 03:03 |
| URI: | http://eprints.um.edu.my/id/eprint/33665 |
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