• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.709-717
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• 2014

The objective of this study is to analyze the degree of correspondences among corners found in building facade imagery when the projective transformation parameters are applied to. Additionally, an appropriate corner detection operator is determined through experiments. Modeling of the shape of a building has been studied in numerous approaches using various type of data such as aerial imagery, aerial lidar scanner imagery, terrestrial imagery, and terrestrial lidar imagery. This study compared the Harris operator with FAST operator and found that the Harris operator is superior in extracting major corner points. After extracting corners using the Harris operator and assessing the degree of correspondence among corners in difference images, real corresponding corners were found to be located in the closest distance. The experiment of the projective transformation with varying corners shows that more corner control points with a good distribution enhances the accuracy of the correspondences.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.1
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• pp.12-22
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• 2016

Lidar-based hazard avoidance landing system for lunar lander calculates hazard cost with respect to the desired local landing area in order to identify hazard and designate safe landing point where the cost is minimum basically using slope and roughness of the landing area. In this case, if the parameters are only considered, chosen landing target can be designated near hazard threatening the lander. In order to solve this problem and select optimal safe landing point, hazard cost based on relative distance to hazard should not be considered as well as cost based on terrain parameters. In this paper, the effect of hazard cost based on relative distance to hazard on safe landing performance was analyzed and it was confirmed that landing site designation with two relative distances to hazard results in the best safe landing performance by an experiment using three-dimensional depth camera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.419-424
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• 2009

This paper show about the possibility of practical application after building VR(virtual reality) data based on Airborne LiDAR data which determines complicated topography quickly for the 3D-GIS construction. In this paper, we collected Airborne LiDAR data, digital map, serial photo and a basic design. The results are expected some effective determination by 3D-GIS construction based on LiDAR data. Hereafter, because the research will be able to be given quickly topography information on ubiquitous environment the field of construction and GIS will be able to be helped.

• Spatial Information Research
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• v.22 no.1
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• pp.75-84
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• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.109-114
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• 2009

Although island is great worth in ecology, environmental conservation and important territory as a national land for developing the marine, the bottom of the sea and also ecological studying field for the ages to come, it has not been managed because of lack of a scientific surveying. In the case of a cadastral record, inaccessible islands have not been registered in current cadastral record because of the limit of surveying technology in 1910. Therefore, a scientific investigation and systematic management about unregistered islands are necessary. But, a airborne laser scanning system is possible to acquire an accurate positions with digital images about inaccessible islands. Therefore, scientific detection of unregistered islands became possible. This paper presented the results of the shoreline extraction around the Heuksan island using Lidar data and the detection of unregistered islands comparing the cadastral map to the ortho-image. Also, we presented the extraction technique of unregistered islands by calculating their positions and areas. As a result, we extracted effectively 16 unregistered islands around the Heuksan island.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.124-132
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• 2017

With the growth of interest in the UAVs, the study of the UAV collision avoidance is in progress. Lidar, Video camera, laser sensor, and ultrasonic sensor may be utilized for collision avoidance of UAV. In this paper, the characteristics of MB 1230 ultrasonic sensor is analyzed through the experiment. When concurrently using multitudinous ultrasonic sensors, ultrasonic sensors do not generate correct measurement values. To solve ultrasonic sensor interference, sequentially transmitting ultrasonics signal is suggested by using 'Enable' signal input of ultrasonic sensor, so by activating each ultrasonic sensor gradually. This proposed solution is also verified by experimentation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.389-397
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• 2006

The purpose of the present paper is to offer an analysis of LiDAR data processing and three dimensional terrain for Geographic Information System (CIS) applications. Generally, LiDAR survey is the method which obtains quantitative and qualitative information of the terrain using airborne laser scanning (ALS). We will get a most topographic data at a Triangular Irregular Network (TIN), Digital Surface Model (DSM) and Digital Elevation Model (DEM) using LiDAR data. We examined many factors such as visibility, hillshade, aspect and slope using DEM and DSM. The analyzing results obtained from each item are thought to be regarded as leading factors in the terrain analysis. It is to be hoped that LiDAR survey will contribute a new approach to the terrain analysis.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.17-22
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• 2019

This paper describes the tracking algorithm performance evaluation for autonomous vehicle using a safety envelope based path. As the level of autonomous vehicle technologies evolves along with the development of relevant supporting modules including sensors, more advanced methodologies for path generation and tracking are needed. A safety envelope zone, designated as the obstacle free regions between the roadway edges, would be introduced and refined for further application with more detailed specifications. In this paper, the performance of the path tracking algorithm based on the generated path would be evaluated under safety envelop environment. In this process, static obstacle map for safety envelope was created using Lidar based vehicle information such as current vehicle location, speed and yaw rate that were collected under various driving setups at Seoul National University roadways. A level of safety was evaluated through CarSim simulation based on paths generated with two different references: a safety envelope based path and a GPS data based one. A better performance was observed for tracking with the safety envelop based path than that with the GPS based one.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.