2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models

Ok, Ali Özgün; Ozdarici-Ok, Asli

doi:10.1080/17538947.2017.1337820

Cited by 29 publications

(26 citation statements)

References 43 publications

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“…Choosing a higher α value suppresses non-symmetric radial features as anticipated; however, the orientation values of symmetric features are also reduced. This problem is mitigated by using the aggregation strategy presented in (Ok and Ozdarici-Ok, 2017). In this study, we aggregate the orientation symmetry results for a series of strictness values, i.e.…”

Section: Dataset Evaluation and Parametersmentioning

confidence: 99%

“…Considering the previous effort in this context, our approach specializes for the detection of citrus trees by taking into account two critical observations: (i) the citrus trees have a symmetric circular shape in general, and we present orientationbased radial symmetry transform (Ok and Ozdarici-Ok, 2017) to extract that information, (ii) the citrus trees present an LM with respect to their close neighbourhood, which we utilize extended maxima transformation (Soille, 1999) to extract LMs from a DSM. Thereafter, we filter out erroneous detections arising from symmetry transform using the LM information.…”

Section: Previous Studiesmentioning

confidence: 99%

“…So far, there has been little attention focussing on the citrus trees (e.g. Fieber et al, 2013;Ozdarici-Ok, 2015;Ok and Ozdarici-Ok, 2017).…”

Section: Previous Studiesmentioning

confidence: 99%

“…However, their approach utilized many ad-hoc thresholds, and further problems associated with their approach are discussed in (Ok and Baseski, 2015), and an improved radial symmetry transform to detect circular objects from images were proposed. More recently, we proposed an orientation-based radial symmetry (Ok and Ozdarici-Ok, 2017) that is particularly designed to focus on above-ground circular objects from a DSM. In the following, we first review that approach, and improve the results of that approach using LM information.…”

Section: Proposed Approachmentioning

confidence: 99%

“…The approach considers the symmetric nature of the citrus trees and detects them from a single source, DSM. In a very recent work, we presented a new form of orientation-based radial symmetry transform (Ok and Ozdarici-Ok, 2017) that can be directly applied to an input like DSM to detect and label the citrus trees. We expand that approach such that false positive detections by the approach are mitigated using additional local maxima (LM) information.…”

Section: Introductionmentioning

confidence: 99%

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Detection of Citrus Trees From Uav DSMS

Ozdarici-Ok

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper presents an automated approach to detect citrus trees from digitals surface models (DSMs) as a single source. The DSMs in this study are generated from Unmanned Aerial Vehicles (UAVs), and the proposed approach first considers the symmetric nature of the citrus trees, and it computes the orientation-based radial symmetry in an efficient way. The approach also takes into account the local maxima (LM) information to verify the output of the radial symmetry. Our contributions in this study are twofold: (i) Such an integrated approach (symmetry + LM) has not been tested to detect (citrus) trees (in orchards), and (ii) the validity of such an integrated approach has not been experienced for an input, e.g. a single DSM. Experiments are performed on five test patches. The results reveal that our approach is capable of counting most of the citrus trees without manual intervention. Comparison to the stateof-the-art reveals that the proposed approach provides notable detection performance by providing the best balance between precision and recall measures.

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Section: Dataset Evaluation and Parametersmentioning

confidence: 99%

Section: Previous Studiesmentioning

confidence: 99%

“…So far, there has been little attention focussing on the citrus trees (e.g. Fieber et al, 2013;Ozdarici-Ok, 2015;Ok and Ozdarici-Ok, 2017).…”

Section: Previous Studiesmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Detection of Citrus Trees From Uav DSMS

Ozdarici-Ok

2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Orchard management with small unmanned aerial vehicles: a survey of sensing and analysis approaches

et al. 2021

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Advances in sensor miniaturization are increasing the global popularity of unmanned aerial vehicle (UAV)-based remote sensing applications in many domains of agriculture. Fruit orchards (the source of the fruit industry chain) require site-specific or even individual-tree-specific management throughout the growing season—from flowering, fruitlet development, ripening, and harvest—to tree dormancy. The recent increase in research on deploying UAV in orchard management has yielded new insights but challenges relating to determining the optimal approach (e.g., image-processing methods) are hampering widespread adoption, largely because there is no standard workflow for the application of UAVs in orchard management. This paper provides a comprehensive literature review focused on UAV-based orchard management: the survey includes achievements to date and shortcomings to be addressed. Sensing system architecture focusing on UAVs and sensors is summarized. Then up-to-date applications supported by UAVs in orchard management are described, focusing on the diversity of data-processing techniques, including monitoring efficiency and accuracy. With the goal of identifying the gaps and examining the opportunities for UAV-based orchard management, this study also discusses the performance of emerging technologies and compare similar research providing technical and comprehensive support for the further exploitation of UAVs and a revolution in orchard management.

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Accuracy Assessment of Pleiades-1 Stereo/Tri-stereo Digital Surface Models: A Case-Study for Citrus Trees

Ozdarici-Ok

Baseski

2018

J Indian Soc Remote Sens

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2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models

Cited by 29 publications

References 43 publications

Detection of Citrus Trees From Uav DSMS

Detection of Citrus Trees From Uav DSMS

Orchard management with small unmanned aerial vehicles: a survey of sensing and analysis approaches

Accuracy Assessment of Pleiades-1 Stereo/Tri-stereo Digital Surface Models: A Case-Study for Citrus Trees

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