• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.119-124
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• 2013

Recent increasing demand on the indoor localization requires more advanced and hybrid technology. This paper proposes an application of the hybrid indoor localization method based on a position-coded pattern that can be used with other existing indoor localization techniques such as vision, beacon, or landmark technique. To reduce the pattern-recognition error rate, the error detection and correction algorithm was applied based on Hamming code. The indoor localization experiments based on the proposed algorithm were performed by using a QCIF-grade CMOS sensor and a position-coded pattern with an area of $1.7{\times}1.7mm^2$. The experiments have shown that the position recognition error ratio was less than 0.9 % with 0.4 mm localization accuracy. The results suggest that the proposed method could be feasibly applied for the localization of the indoor mobile service robots.

• Fashion & Textile Research Journal
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• v.18 no.4
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• pp.468-476
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• 2016

Recent advancements in optics technology enable us to realize fast scans of hands using two-dimensional (2D) image scanners. In this paper, we propose an automatic hand measurement system using 2D image scanners for customized glove production. To develop the automatic hand measurement system, firstly hand scanning devices has been constructed. The devices are designed to block external lights and have user interface to guide hand posture during scanning. After hands are scanned, hand contour is extracted using binary image processing, noise elimination and outline tracing. And then, 19 hand landmarks are automatically detected using an automatic hand landmark detection algorithm based on geometric feature analysis. Then, automatic hand measurement program is executed based on the automatically extracted landmarks and measurement algorithms. The automatic hand measurement algorithms have been developed for 18 hand measurements required for custom-made glove pattern making. The program has been coded using the C++ programming language. We have implemented experiments to demonstrate the validity of the system using 11 subjects (8 males, 3 females) by comparing automatic 2D scan measurements with manual measurements. The result shows that the automatic 2D scan measurements are acceptable in the customized glove making industry. Our evaluation results confirm its effectiveness and robustness.

• Childhood Kidney Diseases
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• v.26 no.1
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• pp.31-39
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• 2022

Alport syndrome (AS) is a progressive hereditary nephritis that is often accompanied by sensorineural hearing loss and ocular abnormalities. It is inherited in three modes of X-linked AS (XLAS), autosomal recessive AS (ARAS), and autosomal dominant AS (ADAS). XLAS is caused by pathogenic variants in COL4A5, while ARAS and ADAS are caused by those in COL4A3 or COL4A4. There is currently no curative treatment for AS; however, angiotensin-converting enzyme inhibitors (ACEi) can improve the outcome of AS. In the past decade, multiple studies have shown that early intervention with ACEi upon isolated microscopic hematuria or microalbuminuria could delay disease progression, and early diagnosis is crucial for early treatment. Therefore, a new classification of AS based on molecular diagnoses has been proposed, including the paradigm shift of re-classifying female "carriers" to "patients" and "thin basement membrane nephropathy" to "ADAS." In addition, with the detection of COL4A mutations in some patients with biopsy-confirmed IgA nephropathy, focal segmental glomerulosclerosis, and chronic kidney disease of unknown origin, it is suggested that the phenotype of AS should be expanded. In this review, we highlight the landmark studies and guidelines published over the past decade and introduce strategies for early diagnosis and treatment to improve the outcomes of AS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.25-31
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• 2020

In this study, for the safe use of a portable ultrasonic skin-beauty device, an android app was developed to show the irradiation locations of focused ultrasound to a user through augmented reality (AR) and enable stable self-surgery. The utility of the app was assessed through testing. While the user is making a facial treatment with the beauty device, the user's face and the ultrasonic irradiation location on the face are detected in real-time with a smart-phone camera. The irradiation location is then indicated on the face image and shown to the user so that excessive ultrasound is not irradiated to the same area during treatment. To this end, ML-Kit is used to detect the user's face landmarks in real-time, and they are compared with a reference face model to estimate the pose of the face, such as rotation and movement. After mounting a LED on the ultrasonic irradiation part of the device and operating the LED during irradiation, the LED light was searched to find the position of the ultrasonic irradiation on the smart-phone screen, and the irradiation position was registered and displayed on the face image based on the estimated face pose. Each task performed in the app was implemented through the thread and the timer, and all tasks were executed within 75 ms. The test results showed that the time taken to register and display 120 ultrasound irradiation positions was less than 25ms, and the display accuracy was within 20mm when the face did not rotate significantly.

• Progress in Medical Physics
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• v.12 no.2
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• pp.177-184
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• 2001

The goal of radiation treatment is to deliver a prescribed radiation dose to the target volume accurately while minimizing dose to normal tissues. Due to inaccurate placement of field and shielding block and patient's movement, there could be displacement errors between the planed and treatment regions. In order to verify the location of radiation treatment, we in this study developed the registration algorithm of the x-ray simulator images and portal images and quantified the inaccuracy in terms of shift, scale and rotation. The algorithm for registration of pairs of radiation fields consists of the alignment of pairs of radiation images by points matching and field displacement analysis by field boundary matching. In the first step, paired surface landmarks are matched to calculate the transformation parameters (scale, rotation and shift) using the corresponding line pairs which are created by connecting two landmarks of each image. In the next step, portal field boundary is extracted and then the two field boundaries are matched by the $\rho$-$\theta$ technique. Applying the phantom portal images, detection errors were calculated to be less than 2mm in translation, 1$^{\circ}$ in rotation and 1% in scale. In conclusion, we quantitatively analyzed the displacement error of x-ray simulator images and portal images. The present results could contribute to the study of the radiation treatment verification.

• Journal of radiological science and technology
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• v.29 no.3
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• pp.125-132
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• 2006

The PET/CT scanner is an evolution in image technology. The two modalities are complementary with CT and PET images. The PET scan images are well known as low resolution anatomic landmak, but such problems may help with interpretation detailed anatomic framework such as that provided by CT scan. PET/CT offers some advantages-improved lesion localization and identification, more accurate tumor staging. etc. Conventional PET employs tranmission scan require around 4 min./bed position and 30 min. for whole body scan. But PET/CT scanner can reduced by 50% in whole body scan. Especially nowadays PET scanner LSO scintillator-based from BGO without septa and operate in 3-D acquisition mode with multidetectors CT. PET/CT scanner fusion problems solved through hardware rather than software. Such device provides with the capability to acquire accurately aligned anatomic and functional images from single scan. It is very important to effective detection from gamma ray source in PETdetector. And can be offer high quality diagnostic images. So we have study about detection processing of PET detector and high quality imaging process.

• The Korean Journal of Nuclear Medicine
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• v.22 no.1
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• pp.83-92
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• 1988

The cocktails of two $^{131}I$ labeled Monoclonal antibody (MCAB) (Anti CA 19-9 F$(ab')_2$ + Anti CEA $F(ab')_2$ fragment), which react specially, with human gastrointestinal cancers, were administered to 10 patients with colorectal (7), stomach(2) and pancreas(1) cancer for scintigraphic detection. All patients were known or postoperatively recurrent cases, and serum tumor markers, CA 19-9 and CEA, were measured with immunoradiometric assay, just before immunoscintigraphy (ISG). The tumor marker's level in serum is not correlated with positive tumor uptake in ISG. The sensitivity and specificity of ISG in detection of 21 tumor sites, based on surgery, CT, ultrasonography and pathology, were 90.5% and 100% One case of colon cancer showed gall bladder metastasis, which was neglected on CT study. Tumor/non tumor uptake ratio of radiolabelled antibody were progressively increased from day 3 to day 7 during study. We summerized as follows 1) The use of cocktails of CEA and CA 19-9 MCAB $F(at')_2$ increased sensitivity and specificity in ISG. 2) Delayed imaging (later than 5 days) increases sensitivitv and specificity due to exclusion of nonspecific iodine accumulation in stomach and lung. 3) Second tracer technique is essential for anatomical landmark by use of a double isotope scan, but subtraction technique, a possible source of artifacts, is no longer necessory when delayed imaging is performed. 4) It may be possible to use two MCAB cocktails of CA 19-9 and CEA in Radioimmunodetection of stomach and pancreas cancer. In conclusion, ISG using MCAB cocktails, $F(ab')_2$ fragment of anti CA 19-9 and Anti CEA, provide additional opportunity for tumor localization and detection of colorectal and other G-I cancer, such as stomach and pancreas.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.1
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• pp.35-45
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• 2007

The log data collected from mobile devices contains diverse meaningful and practical personal information. However, this information is usually ignored because of its limitation of memory capacity, computation power and analysis. We propose a novel method that detects landmarks of meaningful information for users by analyzing the log data in distributed modules to overcome the problems of mobile environment. The proposed method adopts Bayesian probabilistic approach to enhance the inference accuracy under the uncertain environments. The new cooperative modularization technique divides Bayesian network into modules to compute efficiently with limited resources. Experiments with artificial data and real data indicate that the result with artificial data is amount to about 84% precision rate and about 76% recall rate, and that including partial matching with real data is about 89% hitting rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.349-356
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• 2020

This paper introduces the implementation of a driver's condition warning system using eye aspect ratio to prevent a car accident. The proposed driver's condition warning system using eye aspect ratio consists of a camera, that is required to detect eyes, the Raspberrypie that processes information on eyes from the camera, buzzer and vibrator, that are required to warn the driver. In order to detect and recognize driver's eyes, the histogram of oriented gradients and face landmark estimation based on deep-learning are used. Initially the system calculates the eye aspect ratio of the driver from 6 coordinates around the eye and then gets each eye aspect ratio values when the eyes are opened and closed. These two different eye aspect ratio values are used to calculate the threshold value that is necessary to determine the eye state. Because the threshold value is adaptively determined according to the driver's eye aspect ratio, the system can use the optimal threshold value to determine the driver's condition. In addition, the system synthesizes an input image from the gray-scaled and LAB model images to operate in low lighting conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1279-1292
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• 2022

This study proposes a non-contact input method based on face recognition and Pyautogui mouse control as a system that can help users who have difficulty using input devices such as conventional mouse due to physical discomfort. This study includes features that help web surfing more conveniently, especially screen zoom, scroll function, and also solves the problem of eye fatigue, which has been suggested as a limitation in existing non-contact input systems. In addition, various set values can be adjusted in consideration of individual physical differences and Internet usage habits. Furthermore, no high-performance CPU or GPU environment is required, and no separate tracker devices or high-performance cameras are required. Through these studies, we intended to contribute to the realization of barrier-free access by increasing the web accessibility of the disabled and the elderly who find it difficult to use web content.