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פותח על ידי קלירמאש פתרונות בע"מ -
A photogrammetry-based image registration method for multi-camera systems – With applications in images of a tree crop
Year:
2018
Source of publication :
Biosystems Engineering
Authors :
אלחנתי, ויקטור
;
.
Volume :
174
Co-Authors:

Gan, H., Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States; Lee, W.S., Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States

Facilitators :
From page:
89
To page:
106
(
Total pages:
18
)
Abstract:

In precision agriculture, estimating crop yield using remote sensing techniques is an active research field. To achieve high accuracies, researchers frequently combined different imaging sources, such as colour (Red, Green, Blue [RGB]) images, thermal images, and near-infrared images. However, fusing information from those images has been a difficult task. Therefore, accurate image registration methods are necessary. This study aimed to develop a thermal-colour camera system which will register thermal images with colour images of tree canopies in preparation of information fusion and fruit detection. The registration method created in this study was based on photogrammetry. In preparation of registration, a camera system was built, consisting of a thermal camera and two colour cameras. Camera calibration, image intersection, and space resection were combined in a single step named ‘stereo-calibration’ to compute cameras’ parameters and poses. Speeded-up robust features (SURF) were used to find points of interest from colour images. Random sample consensus (RANSAC) was utilised to search for optimal homography transforms between thermal and colour images. In addition, this study created a procedure for accurate registrations of regions of interest in thermal-colour image pairs, utilising structural similarity (SSIM) index. The proposed method offered pixel-level registration accuracy and achieved an average accuracy of 3 pixels in 640 × 480 – pixel citrus canopy images. © 2018 IAgrE

Note:
Related Files :
calibration
color
Crops
Forestry
Infrared imaging
precision agriculture
remote sensing
Thermal analysis
Thermal challenge
עוד תגיות
תוכן קשור
More details
DOI :
10.1016/j.biosystemseng.2018.06.013
Article number:
0
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
35309
Last updated date:
02/03/2022 17:27
Creation date:
17/07/2018 11:06
Scientific Publication
A photogrammetry-based image registration method for multi-camera systems – With applications in images of a tree crop
174

Gan, H., Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States; Lee, W.S., Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States

A photogrammetry-based image registration method for multi-camera systems – With applications in images of a tree crop

In precision agriculture, estimating crop yield using remote sensing techniques is an active research field. To achieve high accuracies, researchers frequently combined different imaging sources, such as colour (Red, Green, Blue [RGB]) images, thermal images, and near-infrared images. However, fusing information from those images has been a difficult task. Therefore, accurate image registration methods are necessary. This study aimed to develop a thermal-colour camera system which will register thermal images with colour images of tree canopies in preparation of information fusion and fruit detection. The registration method created in this study was based on photogrammetry. In preparation of registration, a camera system was built, consisting of a thermal camera and two colour cameras. Camera calibration, image intersection, and space resection were combined in a single step named ‘stereo-calibration’ to compute cameras’ parameters and poses. Speeded-up robust features (SURF) were used to find points of interest from colour images. Random sample consensus (RANSAC) was utilised to search for optimal homography transforms between thermal and colour images. In addition, this study created a procedure for accurate registrations of regions of interest in thermal-colour image pairs, utilising structural similarity (SSIM) index. The proposed method offered pixel-level registration accuracy and achieved an average accuracy of 3 pixels in 640 × 480 – pixel citrus canopy images. © 2018 IAgrE

Scientific Publication
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