• 한국한의학연구원논문집
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• 제14권3호
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• pp.89-95
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• 2008

A tongue shows physiological and clinicopathological changes of inner organs. Visual inspection of a tongue is not only convenient but also non-invasive. To develop an automat ic tongue diagnosis system for an objective and standardized diagnosis, the separation of the tongue are a from a facial image and the detection of coatings, spots and cracks are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth as well as those of tongue furs and body are similar. The propose d method includes preprocessing with down-sampling and edge enhancement, over-segmentation, detecting positions with a local minimum over shading from the structure of a tongue, and correcting local minima or detecting edge with color difference. The proposed method produces the region of a segmented tongue, and then decomposes the color components of the region into hue, saturation and brightness, resulting in classifying the regions of tongue furs(coatings) into kinds of coatings and substance and segmenting them. Spots are detected by using local maxima and the variation of saturation, and cracks are searched by using local minima and the directivity of dark areas in brightness. The results illustrate the segmented region with effective information, excluding a non-tongue region and also give us accurate discrimination of coatings and the precise detection of spots and cracks. It can be used to make an objective and standardized diagnosis for an u-Healthcare system as well as a home care system.

• Investigative Magnetic Resonance Imaging
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• 제21권2호
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• pp.65-70
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• 2017

Purpose: To optimize the saturation time and maximizing the pH-weighted difference between the normal and ischemic brain regions, on 3-tesla amide proton transfer (APT) imaging using an in vivo rat model. Materials and Methods: Three male Wistar rats underwent middle cerebral artery occlusion, and were examined in a 3-tesla magnetic resonance imaging (MRI) scanner. APT imaging acquisition was performed with 3-dimensional turbo spin-echo imaging, using a 32-channel head coil and 2-channel parallel radiofrequency transmission. An off-resonance radiofrequency pulse was applied with a Sinc-Gauss pulse at a $B_{1,rms}$ amplitude of $1.2{\mu}T$ using a 2-channel parallel transmission. Saturation times of 3, 4, or 5 s were tested. The APT effect was quantified using the magnetization-transfer-ratio asymmetry at 3.5 ppm with respect to the water resonance (APT-weighted signal), and compared with the normal and ischemic regions. The result was then applied to an acute stroke patient to evaluate feasibility. Results: Visual detection of ischemic regions was achieved with the 3-, 4-, and 5-s protocols. Among the different saturation times at $1.2{\mu}T$ power, 4 s showed the maximum difference between the ischemic and normal regions (-0.95%, P = 0.029). The APTw signal difference for 3 and 5 s was -0.9% and -0.7%, respectively. The 4-s saturation time protocol also successfully depicted the pH-weighted differences in an acute stroke patient. Conclusion: For 3-tesla turbo spin-echo APT imaging, the maximal pH-weighted difference achieved when using the $1.2{\mu}T$ power, was with the 4 s saturation time. This protocol will be helpful to depict pH-weighted difference in stroke patients in clinical settings.

• 대한전자공학회논문지SP
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• 제43권2호
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• pp.65-72
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• 2006

교통신호등 검출과 인식 시스템은 운전자에게 경고와 보조시스템으로 필요한 장치이다. 본 논문에서는 칼라 비젼시스템을 이용한 주행중 실시간 교통신호등의 검출과 인식법에 대해 제안하고 있다. 제안하는 방법은 크게 네 가지로 구분된다 유사색 환경에서도 신호등 빛 검출이 용이하도록 HSI 색 공간에서 채도와 밝기값의 차를 이용하여 신호등의 빛을 검출하는 신호등 검출, 신호등 외곽검출과 검출된 신호 빛을 바탕으로 교통신호등 외곽 후보영역 설정과 세 검출 결과를 토대로 교통신호등을 인식하는 부분이다. 주행중 영상을 비디오 카메라로 녹화하여 제안하는 방법에 적용하여 결과를 제시하였다. 녹화시 카메라의 줌기능을 이용하여 줌에 의한 입력 영상변화시에도 신호등을 검출 및 인식한 결과를 제시하였다.

• 대한의용생체공학회:의공학회지
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• 제34권2호
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• pp.97-103
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• 2013

This paper proposes a new algorithm for sleep apnea detection based on stroke volume. It is very important to detect sleep apnea since it is a common and serious sleep-disordered breathing (SDB). In the previous studies, methods for sleep apnea detection using heart rate variability, airflow and blood oxygen saturation, tracheal sound have been proposed, but a method using stroke volume has not been studied. The proposed algorithm consists of detection of characteristic points in continuous blood pressure signal, estimation of stroke volume and detection of sleep apnea. To evaluate the performance of algorithm, the MIT-BIH Polysomnographic Database provided by Phsio- Net was used. As a result, the sensitivity of 85.99%, the specificity of 72.69%, and the accuracy of 84.34%, on the average were obtained. The proposed method showed comparable or higher performance compared with previous methods.

• Journal of Information Processing Systems
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• 제10권4호
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• pp.589-601
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• 2014

The performance of edge detection often relies on its ability to correctly determine the dissimilarities of connected pixels. For grayscale images, the dissimilarity of two pixels is estimated by a scalar difference of their intensities and for color images, this is done by using the vector difference (color distance) of the three-color components. The Euclidean distance in the RGB color space typically measures a color distance. However, the RGB space is not suitable for edge detection since its color components do not coincide with the information human perception uses to separate objects from backgrounds. In this paper, we propose a novel method for color edge detection by taking advantage of the HSV color space and the Mahalanobis distance. The HSV space models colors in a manner similar to human perception. The Mahalanobis distance independently considers the hue, saturation, and lightness and gives them different degrees of contribution for the measurement of color distances. Therefore, our method is robust against the change of lightness as compared to previous approaches. Furthermore, we will introduce a noise-resistant technique for determining image gradients. Various experiments on simulated and real-world images show that our approach outperforms several existing methods, especially when the images vary in lightness or are corrupted by noise.

• 비파괴검사학회지
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• 제23권4호
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• pp.356-363
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• 2003

플랜트, 산업용 설비로서 사용되어지고 있는 강관의 결함 검출을 위한 와전류검사장비를 개발하였다. 강관은 내부 불균일 한 전자기적 특성을 포함하고 있는 자성체로서 와전류검사의 응답신호를 왜곡시키므로 이러한 전자기적 특성의 균일화를 위해 자기포화가 요구된다. 자기포화가 없을 경우 결함신호는 잡음신호와 구별되지 않았으나 약 0.62A의 전류가 코일에 가해졌을 때 자기포화되어 결함을 검출 할 수 있었다 자기포화형 탐촉자는 헬름홀츠 코일을 적용하여 제작하였고 내부 대역 통과필터를 이용하여 직류자기장으로 야기되는 잡음신호를 최소화하였다. 개발된 장비를 이용한 현장실험 결과 1m/sec의 이송속도에서 관통홀$({\phi}=2.0mm)$ 결함을 정확히 검출 할 수 있었다.

• 한국전기전자재료학회논문지
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• 제37권3호
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• pp.261-273
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• 2024

This paper is an experimental study on the improvement of smoke and flame detection from different materials with YOLO. For the study, images of fires occurring in various materials were collected through an open dataset, and experiments were conducted by changing the main factors affecting the performance of the fire object detection model, such as the bounding box, polygon, and data augmentation of the collected image open dataset during data preprocessing. To evaluate the model performance, we calculated the values of precision, recall, F1Score, mAP, and FPS for each condition, and compared the performance of each model based on these values. We also analyzed the changes in model performance due to the data preprocessing method to derive the conditions that have the greatest impact on improving the performance of the fire object detection model. The experimental results showed that for the fire object detection model using the YOLOv5s6.0 model, data augmentation that can change the color of the flame, such as saturation, brightness, and exposure, is most effective in improving the performance of the fire object detection model. The real-time fire object detection model developed in this study can be applied to equipment such as existing CCTV, and it is believed that it can contribute to minimizing fire damage by enabling early detection of fires occurring in various materials.

• IEIE Transactions on Smart Processing and Computing
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• 제6권4호
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• pp.237-245
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• 2017

This paper presents a fire detection algorithm using color and motion models from video sequences. The proposed method detects change in color and motion of overall regions for detecting fire, and thus, it can be implemented in both fixed and pan/tilt/zoom (PTZ) cameras. The proposed algorithm consists of three parts. The first part exploits color models of flames and smoke. The candidate regions in the video frames are extracted with the hue-saturation-value (HSV) color model. The second part models the motion information of flames and smoke. Optical flow in the fire candidate region is estimated, and the spatial-temporal distribution of optical flow vectors is analyzed. The final part accumulates the probability of fire in successive video frames, which reduces false-positive errors when fire-like color objects appear. Experimental results from 100 fire videos are shown, where various types of smoke and flames appear in indoor and outdoor environments. According to the experiments and the comparison, the proposed fire detection algorithm works well in various situations, and outperforms the conventional algorithms.

• 대한기계학회논문집B
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• 제31권11호
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• pp.918-925
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• 2007

In this paper, different criteria fur determining hue change time in the hue detection based transient liquid crystals technique were compared. Results showed that methods utilizing threshold of intensity or saturation gave many missing points and quality of the calculated results were strongly depends on the value of threshold. Wider bandwidth in the hue bandwidth method showed better distribution of calculated hue change time, but induced ambiguity in the hue change time. In the time-hue curve fitting method, the distribution of evaluated hue change time was smooth and reasonable, and, by the nature of curve fitting, the noise effect on the hue was successfully considered in calculating of the hue change time. Compared to other methods, it is expected that the time-hue curve fitting method would provide better and accurate hue change time in the hue detection based transient liquid crystals technique.

• Journal of Electrical Engineering and Technology
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• 제9권5호
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• pp.1780-1787
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• 2014

Arterial oxygen saturation ($SpO_2$) monitoring for newborns requires special attention in neonatal intensive care units (NICUs). Newborns have very low photo-plethysmogram (PPG) amplitudes and their body movements are difficult to contain. Hardware design and its associated signal processing algorithms should be robust enough so that faulty measurements can be avoided. In this study, improved designs were implemented to deal with low perfusion, motion artifact, and the influence of ambient light. Dynamic range was increased by using different LED intensities and a feedback system. To minimize the effects of motion artifact and to discard other unqualified data, four additional algorithms were used, which were based on dual-trace detection, continuity of DC level, morphology of PPG, and simultaneity check of $SpO_2$. Our $SpO_2$ system was tested with newborns with normal respiration in the NICU. Our system provided fast, real-time responses and 100% artifact detection was accomplished under 84% of $SpO_2$.