• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.305-315
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• 2010

This research aims to develop a method to determine the 3D coordinates of an object point from overlapping omni-directional images acquired by a ground mobile mapping system and assess their accuracies. In the proposed method, we first define an individual coordinate system on each sensor and the object space and determine the geometric relationships between the systems. Based on these systems and their relationships, we derive a straight line of the corresponding object point candidates for a point of an omni-directional image, and determine the 3D coordinates of the object point by intersecting a pair of straight lines derived from a pair of matched points. We have compared the object coordinates determined through the proposed method with those measured by GPS and a total station for the accuracy assessment and analysis. According to the experimental results, with the appropriate length of baseline and mutual positions between cameras and objects, we can determine the relative coordinates of the object point with the accuracy of several centimeters. The accuracy of the absolute coordinates is ranged from several centimeters to 1 m due to systematic errors. In the future, we plan to improve the accuracy of absolute coordinates by determining more precisely the relationship between the camera and GPS/INS coordinates and performing the calibration of the omni-directional camera

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.92-98
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• 2008

A combination of the instrumented indentation and 3D morphology measurement has been tried in order to perform a real-time property measurement of degraded materials in gas pipelines; three-dimensional indent morphologies were recorded using a reflective laser scanner after a series of insturmented indentations on three metallic specimens. Dimensions of the permanent deformation zone and contact boundary were analyzed from the cross-sectional profile over an remnant indent and used for estimating yield strength and hardness, respectively. Estimated yield strength was comparable with that from uniaxial tensile test and actual hardness implying material pile-up effects was lower than the calculated value from indentation curve by $20{\sim}30%$. It means that this 3D image analysis can explain the material pile-up effects on the contact properties. Additionally, a combined system of indentation and laser sensor was newly designed by modifying a shape of the indentation loading fixture.

• Journal of the Korean Society of Radiology
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• v.8 no.7
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• pp.371-376
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• 2014

The process of flip-chip bump bonding, Au wire bonding and encapsulation were sucessfully developed and modularized. The CdTe sensor and ROIC were optimally jointed together at $150^{\circ}C$ and $270^{\circ}C$ respectively under24.5 N for 30s. To make SnAg bump on ROIC easy to be bonded, the higher bonding temperature was established than CdTe sensor's. In addition, the bonding pressure was lowered minimally because CdTe Sensor is easier to break than Si Sensor. CdTe multi-energy sensor module observed were no electrical failures in the joints using developed flip chip bump bonding and Au wire bonding process. As a result of measurement, shearing force was $2.45kgf/mm^2$ and, it is enough bonding force against threshold force, $2kgf/mm^2s$.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.123-133
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• 2024

Existing autonomous driving technology has been developed based on sensors attached to the vehicles to detect the environment and formulate driving plans. On the other hand, it has limitations, such as performance degradation in specific situations like adverse weather conditions, backlighting, and obstruction-induced occlusion. To address these issues, cooperative autonomous driving technology, which extends the perception range of autonomous vehicles through the support of road infrastructure, has attracted attention. Nevertheless, the real-time analysis of the 3D centroids of objects, as required by international standards, is challenging using single-lens cameras. This paper proposes an approach to detect objects and estimate the centroid of vehicles using the fixed field of view of road infrastructure and pre-measured geometric information in real-time. The proposed method has been confirmed to effectively estimate the center point of objects using GPS positioning equipment, and it is expected to contribute to the proliferation and adoption of cooperative autonomous driving infrastructure technology, applicable to both vehicles and road infrastructure.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.901-908
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• 2013

The introduction of industrial intelligent robot using vision sensor has been interested in automated factory. 2D and 3D vision sensors have used to recognize object and to estimate object pose, which is for packaging parts onto a complete whole. But it is not trivial task due to illumination and various types of objects. Object image has distorted due to illumination that has caused low reliability in recognition. In this paper, recognition method of complex shape object has been proposed. An accurate object region has detected from combined binary image, which has achieved using DoG filter and local adaptive binarization. The object has recognized using neural network, which is trained with sub-divided object class according to object type and rotation angle. Predefined shape model of object and maximal slope have used to estimate the pose of object. The performance has evaluated on ETRI database and recognition rate of 96% has obtained.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.507-513
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• 2021

GPR (Ground Penetrating RADAR) is a sensor that inspects the pavement state of roads, sinkholes, and underground pipes. It is widely used in road management. MMS (Mobile Mapping System) creates a detailed and accurate road map of the road surface and its surroundings. If both types of data are built in the same area, it is efficient to construct both ground and underground spatial information at the same time. In addition, since it is possible to grasp the road and important facilities around the road, the location of underground pipelines, etc. without special technology, an intuitive understanding of the site is also possible, which is a useful tool in managing the road or facilities. However, overseas equipment to which this latest technology is applied is expensive and does not fit the domestic situation. LiDAR (Light Detection And Raging) and GNSS/INS (Global Navigation Satellite System / Inertial Navigation System) were synchronized in order to replace overseas developed equipment and to secure original technology to develop domestic equipment in the future, and GPR data was also synchronized to the same GNSS/INS. We developed software that performs georeferencing using the location and attitude information from GNSS/INS at the time of acquiring synchronized GPR data. The experiments were conducted on the road site by dividing the open sky and the non-open sky. The road and surrounding facilities on the ground could be easily checked through the 3D point cloud data acquired through LiDAR. Georeferenced GPR data could also be viewed with a 3D viewer along with point cloud data, and the location of underground facilities could be easily and quickly confirmed through GPR data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• The Journal of Korean Academy of Prosthodontics
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• v.52 no.2
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• pp.97-104
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• 2014

This study was aimed to compare the radiopacity of four kinds of currently available resin based implant cements using digital radiography. Materials and Methods: Four resin-based implant cements((Estemp $Implant^{TM}$ (Spident, Incheon, Korea), $Premier^{(R)}$Implant (Premier, Pennsylvania, USA), $Cem-Implant^{TM}$ (B.J.M lab, Or-yehuda, Israel), $InterCem^{TM}$ (SCI-PHARM, California, USA)) and control group (Elite Cement $100^{TM}$ (GC, Tokyo, Japan) ) were mixed and cured according to the manufacturer's instructions on the custom made split-type metal mold. A total of 150 specimens of each cement were prepared and each specimen (purity over 99%) was placed side-by-side with an aluminum step wedge for image taking with Intraoral X-ray unit (Esx, Vatech, Korea) and digital X-ray sensor (EzSensor, Vatech, Korea). For the evaluation of aluminum wedge equivalent thickness (mm Al), ImageJ 1.47 m (Wayne Rasband, National Institutes of Health, USA) and Color inspector 3D ver 2.0 (Interaktive Visualisierung von Farbraumen, Berlin, Germany) programs were used. Result: Among the 5 cements, Elite cement $100^{TM}$ (control group) showed the highest radio-opacity in all thickness. In the experimental group, $InterCem^{TM}$ had the highest radio-opacity followed by $Premier^{(R)}$ Implant $Cement^{TM}$, $Cem-Implant^{TM}$ and Estemp $Implant^{TM}$. In addition, $InterCem^{TM}$ showed radio-opacity that met the ISO No. 4049 standard in all the tested specimen thickness. Cem-Implant on 0.5 mm thickness showed radiopacity that met the ISO No. 4049 standard. Conclusion: Among the implant resin-based cements tested in the study, $Premier^{(R)}$ Implant Cement and Estemp $Implant^{TM}$ did not show appropriate radio-opacity. Only $InterCem^{TM}$ and $Cem-Implant^{TM}$ 0.5 mm specimen had the proper radiopacity and met the experiment standard.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.451-463
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• 2022

Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.6
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• pp.735-744
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• 2019

One of the key factors for recognition performance in the automatic target recognition for synthetic aperture radar imagery(SAR-ATR) system is reliability of the SAR target database. To achieve optimal performance, the database should be constructed using the images obtained under the same operating condition as the SAR sensor. However, it is impractical to have the extensive set of real-world SAR images, and thus those from the electro magnetic prediction tool with 3-D CAD models are suggested as an alternative where their reliability can be always questionable. In this paper, a method for similarity assessment between target SAR images is presented inspired by the fact that a target SAR image is mainly characterized by the features of scattering centers. The method is demonstrated using a variety of examples and quantitatively measures the similarity related to reliability. Its assessment performance is further compared with that of the existing metric, structural similarity(SSIM).