• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.61-69
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• 2009

In this paper, to propose a new approach to real-time eye tracking. Existing methods of tracking the user's attention to the little I move my head was not going to get bad results for each of the users needed to perform the calibration process. Infrared eye tracking methods proposed lighting and Generalized Regression Neural Networks (GRNN) By using the calibration process, the movement of the head is large, even without the reliable and accurate eye tracking, mapping function was to enable each of the calibration process by the generalization can be omitted, did not participate in the study eye other users tracking was possible. Experimental results of facial movements that an average 90% of cases, other users on average 85% of the eye tracking results were shown.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.3
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• pp.248-253
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• 2014

Camera calibration is an indispensable process for improving measurement accuracy in industry fields such as machine vision. However, existing calibration cannot be applied to the calibration of mid-wave and long-wave infrared cameras. Recently, with the growing use of infrared thermal cameras that can measure defects from thermal properties, development of an applicable calibration target has become necessary. Thus, based on heat conduction analysis using finite element analysis, we developed a calibration target that can be used with both existing visible cameras and infrared thermal cameras, by implementing optimal design conditions, with consideration of factors such as thermal conductivity and emissivity, colors and materials. We performed comparative experiments on calibration target images from infrared thermal cameras and visible cameras. The results demonstrated the effectiveness of the proposed calibration target.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.577-589
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• 2021

Drone mapping systems can be applied to many fields such as disaster damage investigation, environmental monitoring, and construction process monitoring. To integrate individual sensors attached to a drone, it was essential to undergo complicated procedures including time synchronization. Recently, a variety of composite sensors are released which consist of visual sensors and GPS/INS. Composite sensors integrate multi-sensory data internally, and they provide geotagged image files to users. Therefore, to use composite sensors in drone mapping systems, mapping accuracies from composite sensors should be examined. In this study, we analyzed the mapping accuracies of a composite sensor, focusing on the data acquisition area and pre-calibration effect. In the first experiment, we analyzed how mapping accuracy varies with the number of ground control points. When 2 GCPs were used for mapping, the total RMSE has been reduced by 40 cm from more than 1 m to about 60 cm. In the second experiment, we assessed mapping accuracies based on whether pre-calibration is conducted or not. Using a few ground control points showed the pre-calibration does not affect mapping accuracies. The formation of weak geometry of the image sequences has resulted that pre-calibration can be essential to decrease possible mapping errors. In the absence of ground control points, pre-calibration also can improve mapping errors. Based on this study, we expect future drone mapping systems using composite sensors will contribute to streamlining a survey and calibration process depending on the data acquisition circumstances.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.2
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• pp.108-115
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• 1999

This paper proposes the robot inverse calibration method using a neural networks. A highorder networks called Pi-Sigma networks has been used. The Pi-Sigma networks uses linear summing units in the hidden layer and product unit in output layer. The inverse calibration model which compensates the difference of joint variables only between measuring value and analytic value about the desired pose(position orientation) of a robot is proposed. The compensated values are determined by using the weights obtained from the learning process of the neural networks previously. To prove the reasonableness the SCARA type direct drive robot(4-DOF) and anthropomorphic robot(6-DOF) are simulated. It shows that the proposed calibration method can reduce the errors of the joint variables from $\pm$3 to $\pm$0.1.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.483-488
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• 2003

Calibration and gauge factor readjustment process made for the health monitoring system installed in the railway bridges is reviewed and some findings are explained in this study: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in details. Based on the regression results, new gauge factors are obtained from regression equation and another verification is made by performing another calibration again with new factors. From the second calibration, it was found that the suggested regression curves and their factors are appropriate and much better results are expected. Future work will be concentrated on the long-term analysis of the measurement data and on the database structures so that the assessment of the structure such as damage detection and remaining life estimation is possible.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.34-40
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• 2005

In this paper, we describe the modeling for the 3D robot laser scanning system consisting of a laser stripe projector, camera, and 5-DOF robot and propose its calibration method. Nonlinear radial distortion in the camera model is considered for improving the calibration accuracy. The 3D range data is calculated using the optical triangulation principle which uses the geometrical relationship between the camera and the laser stripe plane. For optimal estimation of the system model parameters, real-coded genetic algorithm is applied in the calibration process. Experimental results show that the constructed system is able to measure the 3D position within about 1mm error. The proposed scheme could be applied to the kinematically dissimilar robot system without losing the generality and has a potential for recognition for the unknown environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.777-787
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• 1995

This paper presents a new method for automatically calibrating robot link (Kinematic) parameters during the process of estimating motion parameters of a moving object. The motion estimation is performed based on stereo cameras mounted on the end-effector of a robot manipulator. This approach significantly differs from other calibration approaches in that the calibration is achieved by simply observing the motion of the moving object (without resorting to any other external calibrating tools) at numerous and widely varying joint-angle configurations. A differential error model, which expresses the measurement errors of a robot in terms of robot link parameter errors and motion parameters, is developed. And then a measurement equation representing the true measurement values is derived. By estimating the above two kinds of parameters minimizing the difference between the measurement equations and the true moving pattern, the calibration of the robot link parameters and the estimation of the motion parameters are accomplished at the same time.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.199-204
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• 1999

The robot inverse calibration method using a neural networks is proposed in this paper. A high-order networks has been used in this study. The Pi-Sigma networks uses linear summing units in the hidden layer and product unit in output layer. The inverse calibration model which compensates the difference of joint variables only between measuring value and analytic value about the desired pose(position orientation) of a robot is proposed. The compensated values are determined by using the weights obtained from the learning process of the neural networks previously. To prove the reasonableness, the selected compliance automatic robot arm type direct drive robot and anthropomorphic robot are simulated. It shows that the proposed calibration method can reduce the errors of the joint variables from ${\pm}$0.15$^{\circ}$to ${\pm}$0.12$^{\circ}$.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.1-7
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• 2016

In this paper, we proposed real-time relative radiometric calibration processing method for SWIR(Short Wavelength Infra-Red) sensor using 'Hyper-Spectral Imager'. Until now domestic research for Hyper-Spectral Imager has been performing with foreign sensor device. So we have been studying hyper spectral sensor device to meet domestic requirement, especially military purpose. To improve detection & identify capability in 'Hyper-Spectral Imager', it is necessary to expend sensing wavelength from visual and NIR(Near Infra-Red) to SWIR. We aimed to design real-time processor for SWIR sensor which can control the sensor ROIC(Read-Out IC) and process calibrate the image. To build Hyper-Spectral sensor device, we will review the SWIR sensor and its signal processing board. And we will analyze relative radiometric calibration processing method and result. We will explain several SWIR sensors, our target sensor and its control method, steps for acquisition of reference images and processing result.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.1 s.343
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• pp.59-64
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• 2006

The slope of the ramp generator in a single slope ADC(analog-to-digital converter) suffers from process and frequency variation. This variation in ramp slope causes ADC gain variation and eventually limits the performance of the ISP(image signal processing) in a CIS(CMOS image sensor) that uses the single slope ADC. This paper proposes a ramp slope BISC(built-in-self-calibration) scheme for CIS. The CIS with proposed BISC was fabricated with a $0.35{\mu}m$ process. The measurement results show that the proposed architecture effectively calibrate the ramp slope against process and clock frequency variation. The silicon area overhead is less than $0.7\%$ of the full chip area.