• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1648-1672
• /
• 2020

There are several types of image registration in the sense of stitching separated images that overlap each other. One of these is feature-based registration by a common feature descriptor. In this study, we generate a mosaic of images using feature-based registration for drone aerial images. As a feature descriptor, we apply the scale-invariant feature transform descriptor. In order to investigate the authenticity of the feature points and to have the mapping function, we employ the sample consensus method; we consider the sensed image's inherent characteristic such as the geometric congruence between the feature points of the images to propose a novel hypothesis estimation of the mapping function of the stitching via some optimally chosen initial candidate inliers in the sample consensus method. Based on the experimental results, we show the efficiency of the proposed method compared with benchmark methodologies of random sampling consensus method (RANSAC); the well-ordering property defined in the context and the extensive stitching examples have supported the utility. Moreover, the sample consensus scheme proposed in this study is uncomplicated and robust, and some fatal miss stitching by RANSAC is remarkably reduced in the measure of the pixel difference.

• Journal of Environmental Science International
• /
• v.30 no.1
• /
• pp.19-28
• /
• 2021

To reduce pollution, decrease the production of carbon dioxide, and to maintain a secure supply of energy, interest continues to grow in the area of renewable energy especially since there is a finite supply of cheap oil. Wind energy is one of the most viable options to consider and supply part of the energy needed to reduce dependence on foreign oil. However, it is difficult to predict the wind speed in an environment with many obstacles such as buildings and trees and getting accurate dimensions of those obstacles is difficult particularly on sloped mountainous terrain. In this study a drone was used to create a 3-D map of the campus of the Catholic University of Pusan. The dimensions and elevations for the 3-D map were used to make a model of the school campus in the CFD program Envi-met. Simulations were run for five different wind directions and 4 different elevations to find the location that would give the highest electrical output for a wind turbine. When considering all of these variables it was found that the optimal location was above the Student Union which had a 40% higher wind speed and could produce 274% more electrical power than the original wind speed.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.411-412
• /
• 2023

The purpose of this research and development is to develop a structure module that improves the efficiency and constructability of the layout structure as well as the design development of rainwater permeable storage tank blocks using inorganic binders and aggregates with the aim of reducing greenhouse gas (CO₂) with eco-friendly materials. In addition, for the efficient response to flooding of the developed permeable storage structure, we present a technical solution for combining drone mapping technology and flood monitoring technology that can analyze topographical factors in detail.

• International Journal of Contents
• /
• v.18 no.3
• /
• pp.74-84
• /
• 2022

The global impact of the Covid-19 pandemic on education has resulted in the near-complete closure of schools, early childhood education and care (ECEC) facilities, universities, and colleges. To help the educational system with social distancing during this pandemic, in this paper the creation of a simple 3D virtual tour will be of a great contribution. This web cyber tour will be program with JavaScript programming language. The development of this web cyber tour is to help the students and staffs to have access to the university infrastructure at a faraway distance during this difficult moment of the pandemic. The drone and matterport are the two devices used in the realization of this website tour. As a result, Users will be able to view a 3D model of the university building (drone) as well as a real-time tour of its inside (matterport) before uploading the model for real-time display by the help of this website tour. Since the users can enjoy the 3D model of the university infrastructure with all angles at a far distance through the website, it will solve the problem of Covid-19 infection in the university. It will also provide students who cannot be present on-site, with detailed information about the campus.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.4
• /
• pp.243-251
• /
• 2019

The road sign location information installed on national roads is continuously updated using MMS (Mobile Mapping System) technology. It is possible to map accurate road facilities by MMS, but the equipment is very expensive and requires specialized technology. Also, the accuracy of the position of the object greatly depends on the GPS (Global Positioning System) accuracy. In the case of road facility mapping, the advantage of drone is more remarkable than that of field survey or conventional aerial photogrammetry. In particular, it is more efficient than field surveying and it is possible to acquire high resolution images with low budget compared to conventional aerial photogrammetry. In this study, the accuracy of the location information measured by the existing MMS is compared with the GPS survey result and the accuracy analysis is performed by the drone aerial photogrammetry. In order to confirm the space accuracy that can be obtained when conducting drone aerial photogrammetry, the accuracy of the change in the number of ground control points and the degree of overlap was evaluated. As a result of the experiment, it was possible to obtain sufficient accuracy with two ground control points distributed at both ends of the road and 60% overlap.

• Journal of Ecology and Environment
• /
• v.41 no.5
• /
• pp.145-151
• /
• 2017

Background: Conventional bird observation methods are line survey or point count method by bare eyes or through binoculars or telescopes. But in this study, the possibility of monitoring waterbirds using drones beyond the conventional research methods was explored. It also describes the direction of producing and accumulating images of waterbird habitats as a method to efficiently determine changes in waterbird habitats. Results: From the study, it was concluded that waterbird monitoring using drones was a new monitoring technique which could be applied to the field and 26 kinds of waterbirds were observed. In the case of a drone with a single lens, it was difficult to identify objects because the size of the subject was too small at a certain altitude. In this case, zoom lens can be an alternative. It has also been verified that image analysis software can be used to accumulate images of waterbird habitats. Conclusions: If various kinds of advanced drones and cameras are used, it would be possible to monitor larger areas including the areas that are difficult for human access and to observe more waterbirds and wider habitats.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.6_3
• /
• pp.1325-1332
• /
• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.3
• /
• pp.127-134
• /
• 2018

Electric transmission towers are facilities to transport electrical power from a plant to an electrical substation. The towers are connected using power lines that are installed with a proper sag by loosening the cable to lower the tension and to secure the sufficient clearance from the ground or nearby objects. The power line sag may extend over the tolerance due to the weather such as strong winds, temperature changes, and a heavy snowfall. Therefore the periodical mapping of the power lines is required but the poor accessibility to the power lines limit the work because most power lines are placed at the mountain area. In addition, the manual mapping of the power lines is also time-consuming either using the terrestrial surveying or the aerial surveying. Therefore we utilized multiple overlapping images acquired from a low-cost drone to automatically reconstruct the power lines in the object space. Two overlapping images are selected for epipolar image resampling, followed by the line extraction for the resampled images and the redundant images. The extracted lines from the epipolar images are matched together and reconstructed for the power lines primitive that are noisy because of the multiple line matches. They are filtered using the extracted line information from the redundant images for final power lines points. The experiment result showed that the proposed method successfully generated parabolic curves of power lines by interpolating the power lines points though the line extraction and reconstruction were not complete in some part due to the lack of the image contrast.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.565-572
• /
• 2018

Recently, UAVs (Unmanned Aerial Vehicles) or drones have gained popularity for the engineering surveying and mapping because they enable the rapid data acquisition and processing as well as their operation cost is low. The applicable fields become much wider including the topographic monitoring, agriculture, and forestry. It is reported that the high geospatial accuracy is achievable with the drone photogrammetry for many applications. However most studies reported the best achievable mapping results using well-distributed ground control points though some studies investigated the impact of control points on the accuracy. In this study, we focused on the drone mapping of corridors such as roads and pipelines. The distribution and the number of control points along the corridor were diversified for the accuracy assessment. In addition, the effects of the camera self-calibration and the number of the image strips were also studied. The experimental results showed that the biased distribution of ground control points has more negative impact on the accuracy compared to the density of points. The prior camera calibration was favored than the on-the-fly self-calibration that may produce poor positional accuracy for the case of less or biased control points. In addition, increasing the number of strips along the corridor was not helpful to increase the positional accuracy.

• Korean Journal of Remote Sensing
• /
• v.40 no.2
• /
• pp.151-166
• /
• 2024

Coastal debris presents a significant environmental threat globally. This research sought to improve the monitoring methods for coastal debris by employing deep learning and remote sensing technologies. To achieve this, an object detection approach utilizing the You Only Look Once (YOLO)v8 model was implemented to develop a comprehensive image dataset for 11 primary types of coastal debris in our country, proposing a protocol for the real-time detection and analysis of debris. Drone imagery was collected over Sinja Island, situated at the estuary of the Nakdong River, and analyzed using our custom YOLOv8-based analysis program to identify type-specific hotspots of coastal debris. The deployment of these mapping and analysis methodologies is anticipated to be effectively utilized in managing coastal debris.