• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.53-59
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• 2024

This study presents the design and implementation of a camera-based 6DoF (6 Degrees of Freedom) tracking and pose estimation system. In particular, we propose a method for accurately estimating the positions and orientations of all fingers of a user utilizing a 6DoF robotic arm. The system is developed using the Python programming language, leveraging the Mediapipe and OpenCV libraries. Mediapipe is employed to extract keypoints of the fingers in real-time, allowing for precise recognition of the joint positions of each finger. OpenCV processes the image data collected from the camera to analyze the finger positions, thereby enabling pose estimation. This approach is designed to maintain high accuracy despite varying lighting conditions and changes in hand position. The proposed system's performance has been validated through experiments, evaluating the accuracy of hand gesture recognition and the control capabilities of the robotic arm. The experimental results demonstrate that the system can estimate finger positions in real-time, facilitating precise movements of the 6DoF robotic arm. This research is expected to make significant contributions to the fields of robotic control and human-robot interaction, opening up various possibilities for future applications. The findings of this study will aid in advancing robotic technology and promoting natural interactions between humans and robots.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.48-56
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• 2014

Purpose $^{99m}Tc$-DTPA renal scintigraphy serves as a key indicator to measure a kidney donor's Glomerular Filtration Rate (GFR) and determine the possibility of kidney transplant. The Gates method utilized to measure GFR considers 3 variables of renal depth, injection dose, and net kidney counts. In this research, we seek to compare changes in kidney donors' GFR according to renal depth measurement methods of the 3 variables. Materials and Methods We investigated 32 kidney donors who had visited the hospital from October, 2013 to March, 2014 and received abdominal CT and $^{99m}Tc$-DTPA GFR examination. With the cross-section image of the CT and the lateral image from a gamma camera, we measured the renal depth and compared with renal depth calculation equations-Tonnesen, Taylor, and Itoh methods. Renal depth-specific GFR was calculated by using Xeleris Ver. 2.1220 of GE. Then the results were compared with MDRD (Modification of Diet Renal Disease) GFRs based on serum creatinine level. Results The renal depths measured based on the CT and gamma camera images showed high correlation. Tonessen equation gave the lowest GFR value while the value calculated by using the renal depth of CT image was the highest with a 16.62% gap. MDRD GFR showed no statistically significant difference among values calculated through Taylor, Itoh, CT and gamma camera renal depth application (P>0.05), but exhibited a statistically significant change in the value based on Tonnesen equation (P<0.05). Conclusion This research has found that, in GFR evaluation in kidney donors by utilizing $^{99m}Tc$-DTPA, Tonnesen equation-based Gates method underestimated the value than the MDRD GFR. Therefore, if a MDRD GFR value shows a huge difference from the actual examination value, using an image-based renal depth measurement, instead of Tonnesen equation applied to Gates method, is expected to give an accurate GFR value to kidney donors.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.578-589
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• 2014

Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.

• Journal of the Korea Concrete Institute
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• v.16 no.6 s.84
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• pp.741-750
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• 2004

Air voids in hardened concrete have an important influence on concrete durability such as freeze-thaw resistance, surface scaling resistance, and water permeability, and they have been characterized by spacing factor Linear traverse and point count methods in ASTM standard have been used in estimating an air void system in hardened concrete. However, these methods require lots of time and efforts, further they are not repeatable. Image analysis method could be utilized In estimating an air void systems in hardened concrete with a developments of microscope, digital camera and computer program. The purpose of this study was to develope image analysis method and provide a guideline by comparing the results from ASTM method and image analysis method. The concerns were at air void content and diameter distribution, air voids system as well as spacing factors. The experimental variables included air content by air entrained agent (0, 0.01, $0.03\%$) and depth of specimen (top, middle, bottom). The result showed that it was possible to calculate spacing factor using image analysis technique, as well as air content, air diameter distribution, and air structure. This study also contributed in developing an reasonable and repeatable image analysis method.

• Journal of Korea Spatial Information System Society
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• v.4 no.2 s.8
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• pp.55-64
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• 2002

VEfficient generation of road data is one of the most important issues in GIS (Geographic Information System). In this paper, we propose a hybrid approach for automatic generation of road data by combining mobile mapping and image processing techniques. Mobile mapping systems have a form of vehicle equipped with CCD camera, GPS, and INS. They can calculate absolute position of objects that appear in acquired image by photogrammetry, but it is labor-intensive and time-consuming. Automatic road detection methods have been studied also by image processing technology. However, the methods are likely to fail because of obstacles and exceptive conditions in the real world. To overcome the problems, we suggest a hybrid method for automatic road generation, by exploiting both GPS/INS data acquired by mobile mapping system and image processing algorithms. We design an estimator to estimate 3-D coordinates of road line and corresponding location in an image. The estimation process reduces complicated image processing operations that find road line. The missing coordinates of road line due to failure of estimation are obtained by cubic spline interpolation. The interpolation is done piecewise, separated by rapid change such as road intersection. We present experimental results of the suggested estimation and interpolation methods with image sequences acquired by mobile mapping system, and show that the methods are effective in generation of road data.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.438-456
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• 2010

Iris recognition uses a unique iris pattern of user to identify person. In order to enhance the performance of iris recognition, it is reported that the diameter of iris region should be greater than 200 pixels in the captured iris image. So, the previous iris system used zoom lens camera, which can increase the size and cost of system. To overcome these problems, we propose a new method of enhancing the accuracy of iris recognition on low-resolution iris images which are captured without a zoom lens. This research is novel in the following two ways compared to previous works. First, this research is the first one to analyze the performance degradation of iris recognition according to the decrease of the image resolution by excluding other factors such as image blurring and the occlusion of eyelid and eyelash. Second, in order to restore a high-resolution iris image from single low-resolution one, we propose a new method based on multiple multi-layered perceptrons (MLPs) which are trained according to the edge direction of iris patterns. From that, the accuracy of iris recognition with the restored images was much enhanced. Experimental results showed that when the iris images down-sampled by 6% compared to the original image were restored into the high resolution ones by using the proposed method, the EER of iris recognition was reduced as much as 0.133% (1.485% - 1.352%) in comparison with that by using bi-linear interpolation

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.329-336
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• 2007

In this paper we propose both the construction of image DB including information on the shooting location and direction of the captured outdoor images and the efficient retrieval method from the DB. Furthermore, for the automatic extraction of the location and direction information, we suggest to have the Digital Camera equipped with an expandable GPS modulo which has a function to calculate the location and direction and also to utilize GPS IFD tags in the EXIF. Then that will make it possible for us to retrieve quickly and precisely the target image with its geography and other objects on the ground included. In the previous retrieval method based only on the location, we eel some extra useless images due to the fact that all the images in the ROI(Region Of Interest) are searched on one condition, radius. However, with the proposed method in this paper, we can not only retrieve all the images selectively within the ROI but also achieve nearly 100% of precision when we search for the target images within DOI(Direction Of Interest) with another condition, direction, added. Applying this method to an image retrieval system, we can classify or retrieve natural images based on the location and direction information, which, in turn, will be vitally useful to diverse industrial fields such as disaster alarm system, fire and disaster prevention system, traffic information system, and so forth.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.377-388
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• 2011

Surface Image Velocimetry (SIV) is a recently-developed discharge measurement instrument. It uses image processing techniques to measure the water surface velocity and estimate water discharge with given cross section. The present study aims to implement a FSIV (Fixed-type Surface Image Velocimetry) at Soojeon Bridge in the Dalcheon. The hardware system consists of two digital cameras, a computer, and a pressure-type water stage gauge. The images taken with the hardware system are sent to a server computer via a wireless internet, and analyzed with a image processing software (SIV software). The estimated discharges were compared with the observed discharges through Goesan dam spillway and index velocity method using ADVM. The computed results showed a good agreement with the observed one, except for the night time. The results compared with discharges through Goesan dam spillway reached around 5~10% in the case of discharge over 30 m3/s, and the results compared with discharges through index velocity method using ADVM reached around 5% in the case of discharge over 200 $m^3/s$. Considering the low cost of the system and the visual inspection of the site situation with the images, the SIV would be fairly good way to measure water discharge in real time.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1044-1050
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• 2021

After the occurrence of several passenger ship accidents in Korea, various systems are being developed for passenger ship safety management. A total of 162 passenger ships operate along the coast of Korea, of which 105 (65 %) are car-ferries with open vehicle decks. The car-ferry has a navigation pattern that passes through 2 to 4 islands. Safety inspections at the departure point(home port) are carried out by the crew, the operation supervisor of the operation management office, and the maritime safety supervisor. In some cases, self-inspections are carried out for safety inspections at layovers. As with any system, there are institutional and practical limitations. To this end, this study was conducted to suggest a method of detecting a vehicle using image processing and linking it to the calculations for ship stability. For vehicle detection, a method using a difference image and one using machine learning were used. However, a limitation was observed in these methods that the vehicle could not be identified due to strong background lighting from the pier and the ship in the cases where the camera was backlit such as during sunset or at night. It appears necessary to secure sufficient image data and upgrade the program for stable image processing.

• Journal of radiological science and technology
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• v.36 no.4
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• pp.291-297
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• 2013

This study is aimed to evaluate the effect of $T_{1/2}$ upon count rates in the analysis of dynamic scan using NaI (Tl) scintillation camera, and suggest a new quality control method with this effects. We producted a point source with $^{99m}TcO_4^-$ of 18.5 to 185 MBq in the 2 mL syringes, and acquired 30 frames of dynamic images with 10 to 60 seconds each using Infinia gamma camera (GE, USA). In the second experiment, 90 frames of dynamic images were acquired from 74 MBq point source by 5 gamma cameras (Infinia 2, Forte 2, Argus 1). There were not significant differences in average count rates of the sources with 18.5 to 92.5 MBq in the analysis of 10 to 60 seconds/frame with 10 seconds interval in the first experiment (p>0.05). But there were significantly low average count rates with the sources over 111 MBq activity at 60 seconds/frame (p<0.01). According to the second analysis results of linear regression by count rates of 5 gamma cameras those were acquired during 90 minutes, counting efficiency of fourth gamma camera was most low as 0.0064%, and gradient and coefficient of variation was high as 0.0042 and 0.229 each. We could not find abnormal fluctuation in $x^2$ test with count rates (p>0.02), and we could find the homogeneity of variance in Levene's F-test among the gamma cameras (p>0.05). At the correlation analysis, there was only correlation between counting efficiency and gradient as significant negative correlation (r=-0.90, p<0.05). Lastly, according to the results of calculation of $T_{1/2}$ error from change of gradient with -0.25% to +0.25%, if $T_{1/2}$ is relatively long, or gradient is high, the error increase relationally. When estimate the value of 4th camera which has highest gradient from the above mentioned result, we could not see $T_{1/2}$ error within 60 minutes at that value. In conclusion, it is necessary for the scintillation gamma camera in medical field to manage hard for the quality of radiation measurement. Especially, we found a tendency that count rate changes over time at this study, and we proved that it can effect $T_{1/2}$. And also, there is need of appropriate phantoms and the method of quality management like this study, because there are not any advice or limitation degrees for domestic medical purpose scintillation camera.