• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.113-121
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• 1999

It is necessary to calibrate measurement systems to enhance its measurement accuracy. The visual sensing system that is presented in our previous work has to be calibrated, too. It is a multiple mirror system for three-dimensional measurement, which is composed of a camera and a series of mirrors. It is important to calibrate the positions and orientations of the mirrors relative to the camera because they have direct influence on the relationship between the image plane and the task space. This paper presents the calibration method for the visual sensing system. To confirm the measurement performance of the implemented system. its measurement accuracy in measuring the locations in three-dimensional space is investigated. A series of experiments for measuring the locations of the circle-shaped marks are performed. Experimental results show that the sensing system can be effectively used for three-dimensional measurement.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.280-287
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• 2001

The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evacuate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth ColorChecker. As a result, the proposed method showed a lower mean square ems between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.182-188
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• 2019

Autonomous mobile robots need SLAM (simultaneous localization and mapping) to look for the location and simultaneously to make the map around the location. In order to achieve visual SLAM, it is necessary to form an algorithm that detects and extracts feature points from camera images, and gets the camera pose and 3D points of the features. In this paper, we propose MPROSAC algorithm which combines MSAC and PROSAC, and compare the performance of optimization method and the filtering method for feature-based monocular visual SLAM. Sparse Bundle Adjustment (SBA) is used for the optimization method and the extended Kalman filter is used for the filtering method.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.362-371
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• 2013

This paper presents a framework of real-time augmented reality on 3-D mobile display with stereo camera tracking. In the framework, camera poses are jointly estimated with the geometric relationship between stereoscopic images, which is based on model-based tracking. With the estimated camera poses, the virtual contents are correctly augmented on stereoscopic images through image rectification. For real-time performance, stereo camera tracking and image rectification are efficiently performed using multiple threads. Image rectification and color conversion are accelerated with a GPU processing. The proposed framework is tested and demonstrated on a commercial smartphone, which is equipped with a stereoscopic camera and a parallax barrier 3-D display.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2160-2174
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• 2011

In this paper, a new technique for color reproduction based on color variation characteristics of digital camera under a dim light condition is proposed. Generally, photographers should adjust a camera exposure properly for obtaining an image with real color tone of subjects. Thus, in case of taking a picture under a dim light condition, the exposure time of a camera has to be relatively longer than the one under a bright light condition. Although images with real color tone of the subject are obtained, the images may get blurred due to the shaky hands of photographer holding the camera. In order to avoid the blur effect, an input image is captured from a camera set as a short exposure time under a dim light condition. Then we propose a method to reproduce color tone of the dim input image. To this end, color variation characteristics which represent color variations of a digital camera are first extracted by analyzing the Macbeth color checker images taken under various exposure values. Then, a color reproduction is performed by an estimation based on the color variation characteristics. Experimental results have shown that the proposed method has achieved better performance of color reproduction, compared with existing methods.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2923-2925
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• 1999

The objective of camera calibration is to determine the internal optical characteristics of camera and 3D position and orientation of camera with respect to the real world. Calibration procedure applicable to general purpose cameras and lenses. The general method to revise the accuracy rate of calibration is using mathematical distortion of lens. The effective og calibration show big difference in proportion to distortion of camera lens. In this paper, we propose the method which calibration distortion model by using neural network. The neural network model implicity contains all the distortion model. We can predict the high accuracy of calibration method proposed in this paper. Neural network can set properly the distortion model which has difficulty to estimate exactly in general method. The performance of the proposed neural network approach is compared with the well-known Tsai's two stage method in terms of calibration errors. The results show that the proposed approach gives much more stable and acceptabke calibration error over Tsai's two stage method regardless of camera resolution and camera angle.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.1-13
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• 2019

The advent of a fourth industrial revolution, built on advances in digital technology, has coincided with studies using various unmanned aerial vehicles (UAVs) being performed worldwide. However, the accuracy of different sensors and their suitability for particular research studies are factors that need to be carefully evaluated. In this study, we evaluated UAV photogrammetry using smart technology. To assess the performance of digital photogrammetry, the accuracy of common procedures for generating orthomosaic images and digital surface models (DSMs) using terrestrial laser scanning (TLS) techniques was measured. Two different type of non-surveying camera(Smartphone camera, fisheye camera) were attached to UAV platform. For fisheye camera, lens distortion was corrected by considering characteristics of lens. Accuracy of orthoimage and DSM generated were comparatively analyzed using aerial and TLS data. Accuracy comparison analysis proceeded as follows. First, we used Ortho mosaic image to compare the check point with a certain area. In addition, vertical errors of camera DSM were compared and analyzed based on TLS. In this study, we propose and evaluate the feasibility of UAV photogrammetry which can acquire 3 - D spatial information at low cost in a construction site.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.650-657
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• 2012

An effective dual-mode camera system(a passive wide-angle camera and a pan-tilt-zoom camera) is proposed in order to improve the performance of visual surveillance. The fixed wide-angle camera is used to monitor large open areas, but the moving objects on the images are too small to view in detail. And, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a specific moving target. However, its FOV (Field of View) is limited when zooming in on a specific target. Therefore, the cooperation of wide-angle and PTZ cameras is complementary. In this paper, we propose an automatic initial set-up algorithm and coordinate transform method from the wide-angle camera coordinate to the PTZ one, which are necessary to achieve the cooperation. The automatic initial set-up algorithm is able to synchronize the views of two cameras. When a moving object appears on the image plane of a wide-angle camera after the initial set-up positioning, the obtained values of the wide-angle camera should be transformed to the PTZ values based on the coordinate transform method. We also develope the PTZ control method. Various in-door and out-door experiments show that the proposed dual-camera system is feasible for the effective visual surveillance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.3
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• pp.265-271
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• 2015

In this study, optical design for small satellite camera equipped with online optical compensation movements has been conducted. Satellite camera equipped with compensation movements at M2 mirror and focal plane can guarantee the MTF performance through the focal plane image stabilization and the on-orbit optical alignment. The designed optical system is schmidt-cassegrain type that has M1 mirror of a diameter 200mm, GSD 3.8m at an altitude of 700km, and 50 % MTF performance. The performance of the designed optical system has been analyzed through the method of ray aberration curve, spot diagram, and MTF. It has been found by the optical performance analysis that the designed optical system satisfies the optical requirements of satellite camera equipped with online optical compensation movements.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.49-58
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• 2014

This paper proposes a new assessment and reliability validation method of Lane Departure Assistance System based on DGPS-GIS by measuring lanes with camera vision. Assessment of lane departure is performed with yaw speed measurement and determination method for false alarm of ISO 17361 and performance validation is executed after generating departure warning boundary line by considering deviation error of LDAS using DGPS. Distance between the wheel and the lane is obtained through line abstraction using Hough transformation of the lane image with camera vision. Evaluation validation is obtained by comparing this value with the distance obtained with LDAS. The experimental result shows that the error of the extracted distance of the LDAS is within 5 cm. Also it proves performance of LDAS based on DGPS-GIS and assures effectiveness of the proposed validation method for system reliability using camera vision.