• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.31-42
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• 2013

This paper proposes a photogrammetric rectification method based on Bayesian approach as a method that eliminates vertical parallax between stereo images to minimize visual fatigue of 3D contents. The image rectification consists of two phases; geometry estimation and epipolar transformation. For geometry estimation, coplanarity-based relative orientation algorithm was used in this paper. To ensure robustness for mismatch and localization error occurred by automation of tie point extraction, Bayesian approach was applied by introducing several prior constraints. As epipolar transformation perspective transformation was used based on condition of collinearity to minimize distortion of result images and modification for input images. Other algorithms were compared to evaluate performance. For geometry estimation, traditional relative orientation algorithm, 8-points algorithm and stereo calibration algorithm were employed. For epipolar transformation, Hartley algorithm and Bouguet algorithm were employed. The evaluation results showed that the proposed algorithm produced results with high accuracy, robustness about error sources and minimum image modification.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.622-627
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• 2018

In this paper, we introduce an integrated augmented reality system using a small camera and a projector. We extract three-dimensional information of an object with a small portable camera and a projector by using a structured light system. We develop the concept of the virtual camera to generalize the projection method so that the image can be projected at a desired position with only the mesh of the object to be projected without computing the mapping between specific point sets. Therefore, it is possible to project not only simple planes but also complex curved surfaces to desired positions without complicated geometric calculation. Based on a robot with a small camera and a projector, it will largely explain the projector-camera system calibration, the calculation of the position of the recognized object, and the image projection method using the virtual camera concept.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.61-70
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• 2017

In This Paper, the Classification Speed of Vehicle Headlight Modules is Improved by a CPU-based Parallel Processing Using OpenMP. Also, a Classification Method of Headlight Modules which Extracts their Features after Revising their Alignment is Proposed. To Analyze the Performance of the Proposed Method, the Discrimination Accuracy and the Processing Speed were Compared with the Method Using Gray Image and the Method Using Line Detection. As the Results of the Analysis, in the Discrimination Accuracy, the Proposed Method and the Line Detection Method Showed good Performance, but the Proposed Method Showed Better Performance than the Line Detection Method by the Processing Speed. Also, the Gray-based Method was the Best in Processing Speed, but the Proposed Method is Better than the Gray-based Method in the Discrimination Accuracy.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.512-514
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• 2004

The Electro-Optical Camera (EOC) is a high spatial resolution, visible imaging sensor which collects visible image data of the earth's sunlit surface and is the primary payload on KOMPSAT-l. The purpose of the EOC payload is to provide high resolution visible imagery data to support cartography of the Korean Peninsula. The EOC is a push broom-scanned sensor which incorporates a single nadir looking telescope. At the nominal altitude of 685Km with the spacecraft in a nadir pointing attitude, the EOC collects data with a ground sample distance of approximately 6.6 meters and a swath width of around 17Km. The EOC is designed to operate with a duty cycle of up to 2 minutes (contiguous) per orbit over the mission lifetime of 3 years with the functions of programmable gain/offset. The EOC has no pointing mechanism of its own. EOC pointing is accomplished by right and left rolling of the spacecraft, as needed. Under nominal operating conditions, the spacecraft can be rolled to an angle in the range from +/- 15 to 30 degrees to support the collection of stereo data. In this paper, the status of EOC such as temperature, dark calibration, cover operation and thermal control is checked and analyzed by continuously monitored state of health (SOH) data and image data during the mission life of 3 years. The aliveness of EOC and operation continuation beyond mission life is confirmed by the results of the analysis.

• Imaging Science in Dentistry
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• v.47 no.4
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• pp.233-239
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• 2017

Purpose: This study was performed to quantify the repeat rate of imaging acquisitions based on different clinical examinations, and to assess the prevalence of error types in intraoral bitewing and periapical imaging using a digital complementary metal-oxide-semiconductor(CMOS) intraoral sensor. Materials and Methods: A total of 8,030 intraoral images were retrospectively collected from 3 groups of undergraduate clinical dental students. The type of examination, stage of the procedure, and reasons for repetition were analysed and recorded. The repeat rate was calculated as the total number of repeated images divided by the total number of examinations. The weighted Cohen's kappa for inter- and intra-observer agreement was used after calibration and prior to image analysis. Results: The overall repeat rate on intraoral periapical images was 34.4%. A total of 1,978 repeated periapical images were from endodontic assessment, which included working length estimation (WLE), trial gutta-percha (tGP), obturation, and removal of gutta-percha (rGP). In the endodontic imaging, the highest repeat rate was from WLE (51.9%) followed by tGP (48.5%), obturation (42.2%), and rGP (35.6%). In bitewing images, the repeat rate was 15.1% and poor angulation was identified as the most common cause of error. A substantial level of intra- and inter-observer agreement was achieved. Conclusion: The repeat rates in this study were relatively high, especially for certain clinical procedures, warranting training in optimization techniques and radiation protection. Repeat analysis should be performed from time to time to enhance quality assurance and hence deliver high-quality health services to patients

• Progress in Medical Physics
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• v.30 no.4
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• pp.160-166
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• 2019

This study examined the clinical use of two newly installed computed tomography (CT) simulators in the Department of Radiation Oncology. The accreditation procedure was performed by the Korean Institute for Accreditation of Medical Imaging. An Xi R/F dosimeter was used to measure the CT dose index for each plug of the CT dose index phantom. Image qualities such as the Hounsfield unit (HU) value of water, noise level, homogeneity, existence of artifacts, spatial resolution, contrast, and slice thickness were evaluated by scanning a CT performance phantom. All test items were evaluated as to whether they were within the required tolerance level. CT calibration curves-the relationship between CT number and relative electron density-were obtained for dose calculations in the treatment planning system. The positional accuracy of the lasers was also evaluated. The volume CT dose indices for the head phantom were 22.26 mGy and 23.70 mGy, and those for body phantom were 12.30 mGy and 12.99 mGy for the first and second CT simulators, respectively. HU accuracy, noise, and homogeneity for the first CT simulator were -0.2 HU, 4.9 HU, and 0.69 HU, respectively, while those for second CT simulator were 1.9 HU, 4.9 HU, and 0.70 HU, respectively. Five air-filled holes with a diameter of 1.00 mm were used for assessment of spatial resolution and a low contrast object with a diameter of 6.4 mm was clearly discernible by both CT scanners. Both CT simulators exhibited comparable performance and are acceptable for clinical use.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.162-170
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• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.20-31
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• 2008

In this paper, we propose a single view-based technique for the estimation of human height and position. Conventional techniques for the estimation of 3D geometric information are based on the estimation of geometric cues such as vanishing point and vanishing line. The proposed technique, however, back-projects the image of moving object directly, and estimates the position and the height of the object in 3D space where its coordinate system is designated by a marker. Then, geometric errors are corrected by using geometric constraints provided by the marker. Unlike most of the conventional techniques, the proposed method offers a framework for simultaneous acquisition of height and position of an individual resident in the image. The accuracy and the robustness of our technique is verified on the experimental results of several real video sequences from outdoor environments.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.598-608
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• 2020

In this paper, we propose a color correction technique for images acquired through a multi-view camera system for acquiring a 3D model. It is assumed that the 3D volume is captured indoors, and the position and intensity of the light is constant over time. 8 multi-view cameras are used, and converging toward the center of the space, so even if the lighting is constant, the intensity and angle of light entering each camera may be different. Therefore, a color optimization function is applied to a color correction chart taken from all cameras, and a color conversion matrix defining a relationship between the obtained 8 images is calculated. Using this, the images of all cameras are corrected based on the standard color correction chart. This paper proposed a color correction method to minimize the color difference between cameras when acquiring an image using 8 cameras of 3D objects, and experimentally proved that the color difference between images is reduced when it is restored to a 3D image.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.207-213
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• 2018

This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.