• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1297-1303
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• 2021

Most thickness measurement techniques using X-ray radiation are unsuitable in field processes involving fast-moving organic films. Herein, we propose a Compton scattering X-ray radiation method, which probes the light elements in organic materials, and a new simple, non-destructive, and non-contact calibration-free real-time film thickness measurement technique by setting up a bench-top X-ray thickness measurement system simulating a field process dealing with thin flexible organic films. The use of X-ray fluorescence and Compton scattering X-ray radiation reflectance signals from films in close contact with a roller produced accurate thickness measurements. In a high-thickness range, the contribution of X-ray fluorescence is negligible, whereas that of Compton scattering is negligible in a low-thickness range. X-ray fluorescence and Compton scattering show good correlations with the organic film thickness (R² = 0.997 and 0.999 for X-ray fluorescence and Compton scattering, respectively, in the thickness range 0-0.5 mm). Although the sensitivity of X-ray fluorescence is approximately 4.6 times higher than that of Compton scattering, Compton scattering signals are useful for thick films (e.g., thicker than ca. 1-5 mm under our present experiment conditions). Thus, successful calibration-free thickness monitoring is possible for fast-moving films, as demonstrated in our experiments.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.3
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• pp.50-57
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• 2010

A high precision air bearing stage has been developed and calibrated. This linear-motor driven stage was designed to transport a glass or wafer with the X and Y following errors in nanometer regime. To achieve this level of precision, bar type mirrors were adopted for real time ${\Delta}X$ and ${\Delta}Y$ laser measurement and feedback control. With the laser wavelength variation and instability being kept minimized through strict environment control, the orthogonality of this type of control system becomes purely dependent upon the surface flatness, distortion, and assembly of the bar mirrors. Compensations for the bar mirror distortions and assembly have been performed using the self-calibration method. As a result, the orthogonality error of the stage was successfully decreased from $0.04^{\circ}$ to 2.48 arcsec.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.593-605
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• 2012

LiDAR systems provide dense and accurate topographic information. A pre-requisite to achieving the potential accuracy of LiDAR is having a proper system calibration, which aims at estimating all the systematic errors in the system measurements and the mounting parameters relating the different components. This paper presents a rigorous and two approximate methods for LiDAR system calibration. The rigorous approach makes use of the LiDAR equation and the system raw measurements. The approximate approaches utilize simplified LiDAR equations using some assumptions, which allow for less strict requirements regarding the raw measurements. The first presented approximate method, denoted as quasi-rigorous, assumes that we are dealing with a vertical platform (i.e., small pitch and roll angles). This method requires time-tagged point cloud and trajectory position data. The second approximate method, denoted as simplified, assumes that we are dealing with parallel strips, vertical platform, and minor terrain elevation variations compared to the flying height above ground. Such method can be performed using the LiDAR point cloud only. Experimental results using a real dataset, whose characteristics deviate to some extent from the utilized assumptions in the approximate methods, are presented to provide a comparative analysis of the outcome from the introduced methods.

• Computers and Concrete
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• v.33 no.5
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.248-254
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• 2006

It is necessary to improve the exactness and adaptation of the working environment for the intelligent robot system. The vision sensor have been studied for a long time at this points. However, it has many processes and difficulties for the real usages. This paper proposes a visual servoing in the virtual environment to support OLP(Off-Line-Programming) path compensation and supplement the problem of complexity of the old kinematical calibration. Initial robot path could be compensated by pixel differences between real and virtual image. This method removes the varies calibrations and 3D reconstruction process in real working space. To show the validity of the proposed approach, virtual space servoing with stereo camera is carried out with WTK and openGL library for a KUKA-6R manipulator and updated real robot path.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.421-433
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• 2006

This paper proposes a method to insert virtual objects into a real video stream based on feature tracking and camera pose estimation from a set of single-camera video frames. To insert or modify 3D shapes to target video frames, the transformation from the 3D objects to the projection of the objects onto the video frames should be revealed. It is shown that, without a camera calibration process, the 3D reconstruction is possible using multiple images from a single camera under the fixed internal camera parameters. The proposed approach is based on the simplification of the camera matrix of intrinsic parameters and the use of projective geometry. The method is particularly useful for augmented reality applications to insert or modify models to a real video stream. The proposed method is based on a linear parameter estimation approach for the auto-calibration step and it enhances the stability and reduces the execution time. Several experimental results are presented on real-world video streams, demonstrating the usefulness of our method for the augmented reality applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1808-1815
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• 2016

Stable operation of the dam and the river is directly related to the life and property of citizens, and hydrological observation data reliability is essential to the safety against disaster. Even though real-time data acquisition with high accuracy is needed for scientific and reliable water resources management, currently operating water gauges installed on the upper and down stream of dams or rivers are not easy to be calibrated or corrected on site to ensure higher reliability. K-water Institute has been operating an international accredited calibration laboratory for flows meters, rainfall and water gauges. Rainfall gauges are calibrated in the fixed standard room or on-site. However, due to the absence of on-site calibration procedure and system, on-site calibration for the water gauges are performed by an external agency. Therefore, a development of standard calibration procedure and system for on-site calibration of water gauges is needed to improve the reliability of observed hydrological data.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.459-465
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• 2022

This paper reports a method to use a wireless sensor network deployed in the field to real-time monitor soil moisture, warning when the moisture level reaches a specific value, and wirelessly controlling an additional device (LED or water supply system, etc.). In addition, we report all processes related to wireless irrigation system, including field deployment of sensors, real-time monitoring using a smartphone, data calibration, and control of additional devices deployed in the field by smartphone. A commercially available open-source Internet of Things (IoT) platform, NodeMCU, was used, which was combined with a 9V battery, LED and soil humidity sensor to be integrated into a portable prototype. The IoT-based soil humidity sensor prototype deployed in the field was installed next to a tree for on-site demonstration for the measurement of soil humidity in real-time for about 30 hours, and the measured data was successfully transmitted to a smartphone via Wifi. The measurement data were automatically transmitted via e-mail in the form of a text file, stored on the web, followed by analyses and calibrations. The user can check the humidity of the soil real-time through a personal smartphone. When the humidity of a soil reached a specific value, an additional device, an LED device, placed in the field was successfully controlled through the smartphone. This LED can be easily replaced by other electronic devices such as water supplies, which can also be controlled by smartphones. These results show that farmers can not only monitor the condition of the field real-time through a sensor monitoring system manufactured simply at a low cost but also control additional devices such as irrigation facilities from a distance, thereby reducing unnecessary energy consumption and helping improve agricultural productivity.

• Agricultural and Biosystems Engineering
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• v.7 no.1
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• pp.8-12
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• 2006

This study was conducted to develop a real-time internal quality evaluation technique for Korean red ginseng using NIR spectroscopy while they were moving to be graded. Internal qualities of Korean red ginseng were defined by color, amount of white core and cavity in the red ginseng. To evaluate the internal quality, PLS (Partial Least Square) model was developed. Spectrum saturation can be occurred when most red ginseng has a sound internal quality expressed by higher light transmittance ratio, but that could not found in the ginseng of internal white core under the same light situation. And, if spectrum saturation is obtained, it is hard to identify the exact information of internal quality. In order to evaluate of the internal quality regardless of having internal normal core or white core, an integral time controlled method was used to obtain traditional spectrum. This procedure was applied in real-time process when red ginseng was moving to be graded in the line. Among the 450 samples including 223 internal normal ginsengs and 227 internal white core ginsengs, 315 ginsengs (70%) were used to develop a calibration model and 135 ginsengs were spent to validate the model. The result of quality evaluation by the model was very good showing SEP and bias were 0.3573 and 0.0310, respectively, and the accuracy was 95.6%.

• Journal of IKEEE
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• v.20 no.4
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• pp.420-423
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• 2016

In this paper, we proposed an implementation of panoramic image stitching that operates in real time at the embedded environment by applying ROI based PROSAC algorithm using the directionality of the image. The conventional panoramic image stitching applies SURF or SIFT algorithm which contains unnecessary computation and a lots of data to detect feature points. In this paper, we use the direction of the input image and we proposed the method of reducing the unnecessary computation by using ROI. We use a gyro sensor and an acceleration sensor. Output data from gyro and acceleration sensors can be calibrated by complementary filter. The calibration does not affect the operating time of the proposed image stitching algorithm in embedded environment. Therefore, it is possible to operate in real-time.