• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1095-1106
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• 2020

In this paper, we propose an algorithm that extracts a high-precision 3D skeleton using a model generated using a distributed RGB-D camera. When information about a 3D model is extracted through a distributed RGB-D camera, if the information of the 3D model is used, a skeleton with higher precision can be obtained. In this paper, in order to improve the precision of the 2D skeleton, we find the conditions to obtain the 2D skeleton well using the PCA. Through this, high-quality 2D skeletons are obtained, and high-precision 3D skeletons are extracted by combining the information of the 2D skeletons. Even though this process goes through, the generated skeleton may have errors, so we propose an algorithm that removes these errors by using the information of the 3D model. We were able to extract very high accuracy skeletons using the proposed method.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.143-152
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• 2022

The purpose of this paper is to investigate the impact of several factors on students' decisions to attend a public institution in Vietnam's North Central area. The enrollment issue toward regional institutions is particularly critical in the Vietnam Ministry of Education and Training reforming the university enrollment process and the complicated scenario of the Covid-19 pandemic. A total of 500 students were surveyed for research samples. Data is synthesized, validated, cleaned, and analyzed using SPSS and AMOS software using methods including reliability, EFA, CFA, and SEM. The findings suggest that the proposed independent components (individual factors, study fees, advertisement, infrastructure and facilities, local features, and lastly, training activities) have a beneficial impact on students' decision to attend a public university in the North Central region. The study also found that the graduation exam outcome had a moderating effect on the relationship between registration and students' decisions. These imply targeted solutions for regional public universities to diversify training majors, improve training quality, capitalize on local advantages, increase interaction, and promote training programs and image to be more effective in attracting students and maintaining competition in the current enrollment environment.

• Smart Structures and Systems
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• v.32 no.4
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• pp.207-218
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• 2023

Real-time monitoring of the behavior of reinforced soil retaining wall (RSW) is required for safety checks. In this study, a targetless displacement measurement technology (TDMT) consisting of an image registration module and a displacement calculation module was proposed to monitor the behavior of RSW, in which facing displacement and settlement typically occur. Laboratory and field experiments were conducted to compare the measuring performance of natural target (NT) with the performance of artificial target (AT). Feature count- and location-based performance metrics and displacement calculation performance were analyzed to determine their correlations. The results of laboratory and field experiments showed that the feature location-based performance metric was more relevant to the displacement calculation performance than the feature count-based performance metric. The mean relative errors of the TDMT were less than 1.69 % and 5.50 % for the laboratory and field experiments, respectively. The proposed TDMT can accurately monitor the behavior of RSW for real-time safety checks.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.7-11
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• 2023

In this study, we presented a method to recognize vehicle license plates using CNN techniques. A vehicle plate is normally used for the official identification purposes by the authorities. Most regular Optical Character Recognition (OCR) techniques perform well in recognizing printed characters on documents but cannot make out the registration number on the number plates. Besides, the existing approaches to plate number detection require that the vehicle is stationary and not in motion. To address these challenges to number plate detection we make the following contributions. We create a database of captured vehicle number plate's images and recognize the number plate character using Convolutional Neural Networks. The results of this study can be usefully used in parking management systems and enforcement cameras.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.199-206
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• 2024

The GEO-KOMPSAT-2A (GK2A) satellite, which was launched in December 2018, carries weather observation payloads and uses the image navigation and registration system to calibrate the observation images. The calibration system requires accurate orbit prediction data and depends on the accuracy of the orbit determination accuracy. In order to find a possible way to improve the current orbit determination accuracy of the GK2A flight dynamic subsystem module, orbit determination software was developed to independently evaluate the orbit determination accuracy. A comprehensive satellite dynamic model is applied for a batch-type least squares filter. When determining the orbit, thrust firing during station-keeping maneuvers and wheel-off loading maneuvers is taken into account. One month of GK2A ranging data were processed to estimate the satellite position on a daily basis. The orbit determination error was evaluated by comparing estimates during overlapping estimation intervals.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.22-37
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• 2018

Unmanned aerial vehicles (UAV) have attracted considerable attention both at home and abroad. The UAV is equipped with a camera that shoots images, which is advantageous for access to areas where archaeological investigations are not possible. Moreover, it is possible to acquire three-dimensional spatial image information by modeling the terrain through aerial photographing, and it is possible to specify the interpretation of the terrain of the survey area. In addition, if we understand the change of the terrain through comparison with past aerial photographs, it will be very helpful to grasp the existence of the ruins. The terrain modeling for searching these remains can be divided into two parts. First, we acquire the aerial photographs of the current terrain using the drone. Then, using image registration and post-processing, we complete the image-joining and terrain-modeling using past aerial photographs. The completed modeled terrain can be used to derive several analytical results. In the present terrain modeling, terrain analysis such as DSM, DTM, and altitude analysis can be performed to roughly grasp the characteristics of the change in the form, quality, and micro-topography. Past terrain modeling of aerial photographs allows us to understand the shape of landforms and micro-topography in wetlands. When verified with actual findings and overlapping data on the modelling of each terrain, it is believed that changes in hill shapes and buried Microform can be identified as helpful when used in low-flying applications. Thus, modeling data using aerial photographs is useful for identifying the reasons for the inability to carry out archaeological surveys, the existence of terrain and ruins in a wide area, and to discuss the preservation process of the ruins. Furthermore, it is possible to provide various themes, such as cadastral maps and land use maps, through comparison of past and present topographical data. However, it is certain that it will function as a new investigation methodology for the exploration of ruins in order to discover archaeological cultural properties.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.137-143
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• 2013

The high resolution satellite images are used in many fields such as weather observation, remote sensing, military facilities monitoring, cultural properties protection etc. Although satellite images are obtained in same satellite imaging system, the satellite images are degraded depending on the condition of hardware(optical device, satellite operation altitude, image sensor, etc.). Due to the fact that changing the hardware of satellite imaging system is impossible for resolution enhancement of these degraded satellite after launching a satellite, therefore the method of resolution enhancement with satellite images is necessary. In this paper the resolution is enhances by using a Super Resolution(SR) algorithm. The SR algorithm is an algorithm to enhance the resolution of an image by uniting many low resolution images, so an output image has higher resolution than using other interpolation methods. But It is difficult to obtain many images of the same area. Therefore, to solve this problem, we applied SR after by applying the affine and projection transform. As a results, we found that the images applied SR after affine and projection transform have higher resolution than the images only applied SR.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.2
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• pp.153-163
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• 2008

Medical imaging modalities to image either anatomical structure or functional processes have developed along somewhat independent paths. Functional images with single photon emission computed tomography (SPECT) and positron emission tomography (PET) are playing an increasingly important role in the diagnosis and staging of malignant disease, image-guided therapy planning, and treatment monitoring. SPECT and PET complement the more conventional anatomic imaging modalities of computed tomography (CT) and magnetic resonance (MR) imaging. When the functional imaging modality was combined with the anatomic imaging modality, the multimodality can help both identify and localize functional abnormalities. Combining PET with a high-resolution anatomical imaging modality such as CT can resolve the localization issue as long as the images from the two modalities are accurately coregistered. Software-based registration techniques have difficulty accounting for differences in patient positioning and involuntary movement of internal organs, often necessitating labor-intensive nonlinear mapping that may not converge to a satisfactory result. These challenges have recently been addressed by the introduction of the combined PET/CT scanner and SPECT/CT scanner, a hardware-oriented approach to image fusion. Combined PET/CT and SPECT/CT devices are playing an increasingly important role in the diagnosis and staging of human disease. The paper will review the development of multi modality instrumentations for clinical use from conception to present-day technology and the application software.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.323-328
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• 2004

The development of group-specific tissue probability maps (TPM) provides a priori knowledge for better result of cerebral tissue classification with regard to the inter-ethnic differences of inter-subject variability. We present sequential procedures of group-specific TPM and evaluate the age effects in the structural differences of TPM. We investigated 100 healthy volunteers with high resolution MRI scalming. The subjects were classified into young (60, 25.92+4.58) and old groups (40, 58.83${\pm}$8.10) according to the age. To avoid any bias from random selected single subject and improve registration robustness, average atlas as target for TPM was constructed from skull-stripped whole data using linear and nonlinear registration of AIR. Each subject was segmented into binary images of gray matter, white matter, and cerebrospinal fluid using fuzzy clustering and normalized into the space of average atlas. The probability images were the means of these binary images, and contained values in the range of zero to one. A TPM of a given tissue is a spatial probability distribution representing a certain subject population. In the spatial distribution of tissue probability according to the threshold of probability, the old group exhibited enlarged ventricles and overall GM atrophy as age-specific changes, compared to the young group. Our results are generally consistent with the few published studies on age differences in the brain morphology. The more similar the morphology of the subject is to the average of the population represented by the TPM, the better the entire classification procedure should work. Therefore, we suggest that group-specific TPM should be used as a priori information for the cerebral tissue classification.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.115-122
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• 2022

Recently, the importance of CPR training for the layperson has been emphasized to improve the survival rate of out-of-hospital cardiac arrest patients. An accurate and realistic training strategy is required for the CPR training effect for laypersons. In this study, we develop an extended reality (XR) based CPR training system and evaluate its usability. The XR based CPR training system consisted of three applications. First, a 3D heart anatomy image registered to the manikin is transmitted to the smart glasses to guide the chest compression point. The second application provides visual and auditory information about the CPR process through smart glasses. At the same time, the smartwatch sends a vibration notification to guide the compression rate. The 'Add-on-kit' is a device that detects the depth and speed of chest compression via sensors installed on the manikin and sends immediate feedback to the smartphone. One hundred laypersons who participated in this study agreed that the XR based CPR training system has realism and effectiveness. XR based registration technology will contribute to improving the efficiency of CPR training by enhancing realism, immersion, and self-directed learning.