• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.25 no.1
• /
• pp.19-30
• /
• 2007

Modeling 3D buildings is an essential process to revive the real world into a computer. There are two ways to create a 3D building model. The first method is to use the building layer of 1:1000 digital maps based on high density point data gained from airborne laser surveying. The second method is to use LiDAR point data with digital images achieved with LiDAR. In this research we tested one sheet area of 1:1000 digital map with both methods to process a 3D building model. We have developed a process, analyzed quantitatively and evaluated the efficiency, accuracy, and reality. The resulted differed depending on the buildings shape. The first method was effective on simple buildings, and the second method was effective on complicated buildings. Also, we evaluated the accuracy of the produced model. Comparing the 3D building based on LiDAR data and digital image with digital maps, the horizontal accuracy was within ${\pm}50cm$. From the above we derived a conclusion that 3D building modeling is more effective when it is based on LiDAR data and digital maps. Using produced 3D building modeling data, we will be utilized as digital contents in various fields like 3D GIS, U-City, telematics, navigation, virtual reality and games etc.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1023-1030
• /
• 2023

FMCW LiDAR system with robust target detection capabilities even under adverse operating conditions such as snow, rain, and fog is addressed in this paper. Our focus is primarily on enhancing the performance of FMCW LiDAR by improving the characteristics of the frequency-modulated laser, which directly influence range resolution, coherence length, and maximum measurement range etc. of LiDAR. We describe the utilization of an unbalanced Mach-Zehnder laser interferometer to measure real-time changes of the lasing frequency and to correct frequency modulation errors through an optical phase-locked loop technique. To extend the coherence length of laser, we employ an extended-cavity laser diode as the laser source and implement a laser interferometer with an photonic integrated circuit for miniaturization of optical system. The developed FMCW LiDAR system exhibits a bandwidth of 10.045GHz and a remarkable distance resolution of 0.84mm.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.191-199
• /
• 2023

In this paper, we propose a method to extract the features of five sensor-only facilities built as infrastructure for autonomous cooperative driving, which are from point cloud data acquired by LiDAR. In the case of image acquisition sensors installed in autonomous vehicles, the acquisition data is inconsistent due to the climatic environment and camera characteristics, so LiDAR sensor was applied to replace them. In addition, high-intensity reflectors were designed and attached to each facility to make it easier to distinguish it from other existing facilities with LiDAR. From the five sensor-only facilities developed and the point cloud data acquired by the data acquisition system, feature points were extracted based on the average reflective intensity of the high-intensity reflective paper attached to the facility, clustered by the DBSCAN method, and changed to two-dimensional coordinates by a projection method. The features of the facility at each distance consist of three-dimensional point coordinates, two-dimensional projected coordinates, and reflection intensity, and will be used as training data for a model for facility recognition to be developed in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.3
• /
• pp.160-174
• /
• 2023

LiDAR plays a key role in autonomous vehicles, and to improve its visibility, it is necessary to improve its performance and the detection objects. Accordingly, this study proposes a shape for traffic safety signs that is advantageous for self-driving vehicles to recognize. Improvement plans are also proposed using a shape-recognition algorithm based on point cloud data collected through LiDAR sensors. For the experiment, a DBSCAN-based road-sign recognition and classification algorithm, which is commonly used in point cloud research, was developed, and a 32ch LiDAR was used in an actual road environment to conduct recognition performance tests for 5 types of road signs. As a result of the study, it was possible to detect a smaller number of point clouds with a regular triangle or rectangular shape that has vertical asymmetry than a square or circle. The results showed a high classification accuracy of 83% or more. In addition, when the size of the square mark was enlarged by 1.5 times, it was possible to classify it as a square despite an increase in the measurement distance. These results are expected to be used to improve dedicated roads and traffic safety facilities for sensors in the future autonomous driving era and to develop new facilities.

• Journal of the Korea Organic Resources Recycling Association
• /
• v.32 no.1
• /
• pp.39-47
• /
• 2024

In this study, LiDAR-detective black material is synthesized by recycling silicon sludge (SS) that is generated from semiconductor manufacturing process, and its recognition is confirmed using two types of LiDAR sensors (MEMS and Rotating LiDAR). In detail, metal impurities on the surface of SS is removed, followed by coating of titanium dioxide (TiO₂) and subsequent chemical reduction to obtain SS-derived black TiO₂ (SS/bTiO₂) material. As-prepared SS/bTiO₂ is mixed with transparent paint to prepare hydrophilic black paints and applied to a glass substrate using a spray gun. SS/bTiO₂-based paint shows similar blackness (L^*=15.7) compared to commercial carbon black-based paint, and remarkable NIR reflectance (26.5R%, 905nm). Furthermore, MEMS and Rotating LiDAR have successfully detected the SS/bTiO₂-based paint. This is attributed to the occurrence of high reflection of light at the interface between the black TiO₂ and the silicon sludge according to the Fresnel's reflection principle. Hence, the new application field to effectively recycle silicon sludge generated in the semiconductor manufacturing process has been presented.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.4
• /
• pp.504-510
• /
• 2019

Practical test items were analyzed to extend the existing scoring method for boat operator licenses to an electronic scoring method. We have attempted to digitize the method within the current practical test system scope and have developed an electronic scoring system using LiDAR sensors and WAVE communication. The results of the study are as follows; the first, the scoring data entered into the LiDAR and examiner score device on the boat were transferred from an integrated processing unit to a land control center through WAVE communication. The system was constructed and verified to store and manage examinee data. Second, when testing the meandering task, accurate distance measurement was achieved by using LiDAR instead of visually observing the stick (3 m), and an accurate distance was displayed through the examiner score device quickly. Finally, we confirmed that it is possible to smoothly transmit and process the WAVE communication used to transfer the score data acquired from the boat to the monitoring center at a high speed without loss.

• Journal of the Institute of Convergence Signal Processing
• /
• v.19 no.2
• /
• pp.54-60
• /
• 2018

In this paper, we propose an efficient automatic control method for the collision avoidance of drones. In general, the drones are controlled by transmitting to the flight control (FC) module the received PWM signals transmitted from a RC controller which transduce movements of the knob into PWM signal. We implemented the collision avoidance module in-between receiver and FC module to monitor and change the throttle, pitch and roll control signals to avoid drone collision. In order to avoid the collision, a LiDAR distance sensor and a servo-motor are installed and periodically measure the obstacle distance within -45 degrees from 45 degrees in flight direction. If the collision is predicted, the received PWM signal is changed and transmitted to the FC module to prevent the collision. We applied our proposed method to a hexacopter and the experimental results show that the safety is improved because it can prevent the collision caused by the inadvertency or inexperienced maneuver.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.6
• /
• pp.1-15
• /
• 2017

Recently terrorism targets unspecified masses and causes massive destruction, which is so-called Super Terrorism. Many countries have tried hard to protect their citizens with various preparation and safety net. With inexpensive and advanced technologies of sensors, the surveillance systems have been paid attention, but few studies associated with the classification of the pedestrians' trajectories and the difference among themselves have attempted. Therefore, we collected individual trajectories at Samseoung Station using an analytical solution (system) of pedestrian trajectory by LiDAR sensor. Based on the collected trajectory data, a comprehensive framework of classifying the types of pedestrians' trajectories has been developed with data normalization and "trajectory association rule-based algorithm." As a result, trajectories with low similarity within the very same cluster is possibly detected.

• Journal of Broadcast Engineering
• /
• v.24 no.4
• /
• pp.580-591
• /
• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• Proceedings of KOSOMES biannual meeting
• /
• 2018.06a
• /
• pp.6-6
• /
• 2018