• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.415-419
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• 1996

This paper presents motor speed and phase angle detection method using a sinusoidal AC tachogenerator. The 2-phase or 3-phase output tacho-generator can be adopted, and its' output voltages must have sinusoidal waveforms. Because the detection algorithm is simple, the proposed method can be implemented with analog devices of microprocessor conveniently. And the proposed method has a very short detection delay time. Especially in the analog implementation, there is no delay time without the settling time of analog devices. With the Experimental results, it is verified that the proposed method can accurately detect the instantaneous motor speed and phase over the wide ranges.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1416-1423
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• 2017

Lane detection technology is one of the most important issues on car safety and self-driving capability of autonomous vehicle. This paper introduces an accurate lane detection scheme based on OCC(Optical Camera Communication) for moving vehicles. For lane detection of moving vehicles, the streetlights and the front camera of the vehicle were used for a transmitter and a receiver, respectively. Based on the angle information of multiple streetlights in a captured image, the distance from sidewalk can be calculated using non-linear regression analysis. Simulation results show that the proposed scheme shows robust performance of accurate lane detection.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.1
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• pp.27-32
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• 2017

This paper presents a Daubechies wavelet-based fault detection method for fault identification in transmission lines. After the Daubechies wavelet coefficients are calculated, the proposed algorithm has been implemented difference equation using C language. We have modeled a 154kV transmission line using the ATPDraw software and have acquired test data. In order to evaluate effects of DC offset, simulations carried out while varying an inception angle of the voltage $0^{\circ}$, $45^{\circ}$, $90^{\circ}$. For performance evaluation, fault distance was varied. As we can see from the off-line simulation, the proposed algorithm shows rapid and accurate fault detection. Also we can see the proposed algorithm is not affected by the fault inception angle change.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1052-1061
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• 2018

In this paper, we propose a new algorithm that is robust against the effects of objects that are relatively unaffected by camera motion and can accurately detect camera motion even in high resolution images. First, for more accurate camera motion detection, a global motion filter based on entropy of a motion vector is used to distinguish the background and the object. A block matching algorithm is used to find exact motion vectors. In addition, a matched filter with the angle of the ideal motion vector of each block is used. Motion vectors including 4 kinds of diagonal direction, zoom in, and zoom out are added additionally. The experiment shows that the precision, recall, and accuracy of camera motion detection compared to the recent results is improved by 12.5%, 8.6% and 9.5%, respectively.

• Journal of IKEEE
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• v.25 no.4
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• pp.619-624
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• 2021

Vehicle orientation detection is a challenging task because the orientations of vehicles can vary in a wide range in captured images. The existing methods for oriented vehicle detection require too much computation time to be applied to a real-time system. We propose Rotate YOLO, which has a set of anchor boxes with multiple scales, ratios, and angles to predict bounding boxes. For estimating the orientation angle, we applied angle-related IoU with CIoU loss to solve the underivable problem from the calculation of SkewIoU. Evaluation results on three public datasets DLR Munich, VEDAI and UCAS-AOD demonstrate the efficiency of our approach.

• Clinical and Experimental Pediatrics
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• v.60 no.9
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• pp.290-295
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• 2017

Purpose: Airway pathology in children with atopic asthma can be reflected by the concave shape of the maximal expiratory flow-volume (MEFV) curve and high fractional exhaled nitric oxide (FeNO) values. We evaluated the capacity of the curvilinearity of the MEFV curve, FeNO, and their combination to distinguish subjects with atopic asthma from healthy individuals. Methods: FeNO and angle ${\beta}$, which characterizes the general configuration of the MEFV curve, were determined in 119 steroid-naïve individuals with atopic asthma aged 8 to 16 years, and in 92 age-matched healthy controls. Receiver operating characteristic (ROC) curve analyses were performed to determine the cutoff points of FeNO and angle ${\beta}$ that provided the best combination of sensitivity and specificity for asthma detection. Results: Asthmatic patients had a significantly smaller angle ${\beta}$ and higher FeNO compared with healthy controls (both, P<0.001). For asthma detection, the best cutoff values of angle ${\beta}$ and FeNO were observed at $189.3^{\circ}$ and 22 parts per billion, respectively. The area under the ROC curve for the combination of angle ${\beta}$ and FeNO improved to 0.91 (95% confidence interval [CI], 0.87-0.95) from 0.80 (95% CI, 0.75-0.86; P<0.001) for angle ${\beta}$ alone and 0.86 (95% CI, 0.82-0.91; P=0.002) for FeNO alone. In addition, the combination enhanced sensitivity with no significant decrease in specificity. Conclusion: These data suggest that the combined use of the curvilinearity of the MEFV curve and FeNO is a useful tool to differentiate between children with and without atopic asthma.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1841-1857
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• 2023

CenterNet, a novel object detection algorithm without anchor based on key points, regards the object as a single center point for prediction and directly regresses the object's height and width. However, because the objects have different sizes, directly regressing their height and width will make the model difficult to converge and lose the intrinsic relationship between object's width and height, thereby reducing the stability of the model and the consistency of prediction accuracy. For this problem, we proposed an algorithm based on the regression of the diagonal half-length and the center angle, which significantly compresses the solution space of the regression components and enhances the intrinsic relationship between the decoded components. First, encode the object's width and height into the diagonal half-length and the center angle, where the center angle is the angle between the diagonal and the vertical centreline. Secondly, the predicted diagonal half-length and center angle are decoded into two length components. Finally, the position of the object bounding box can be accurately obtained by combining the corresponding center point coordinates. Experiments show that, when using CenterNet as the improved baseline and resnet50 as the Backbone, the improved model achieved 81.6% and 79.7% mAP on the VOC 2007 and 2012 test sets, respectively. When using Hourglass-104 as the Backbone, the improved model achieved 43.3% mAP on the COCO 2017 test sets. Compared with CenterNet, the improved model has a faster convergence rate and significantly improved the stability and prediction accuracy.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.4
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• pp.323-329
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• 2013

This perform research of angle rated defect detection conditions and nuclear power plant piping defect detection by lock-In infrared thermography technique. Defects were processed according to change for wall-thinning length, Circumference orientation angle and wall-thinning depth. In the used equipment IR camera and two halogen lamps, whose full power capacitany is 1 kW, halogen lamps and target pipe's distance fixed 2 m. To analysis of the experimental results ensure for the temperature distribution data, by this data measure for defect length. Reliability of lock-In infrared thermography data is higher than Infrared thermography data. This through research, Shape of angle rated defect is identified industry place. It help various angles defect detection in the nuclear power plant in operation.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.395-401
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• 2020

In this paper, a motion-based ROI extraction algorithm from a high resolution fisheye image is proposed for multi-view monitoring systems. Lately fisheye cameras are widely used because of the wide angle-of-view and they basically provide a lens correction functionality as well as various viewing modes. However, since the distortion-free angle of conventional algorithms is quite narrow due to the severe distortion ratio, there are lots of unintentional dead areas and they require much computation time in finding undistorted coordinates. Thus, the proposed algorithm adopts an image decimation and a motion detection methods, that can extract the undistorted ROI image with a standard angle-of-view for the fast and intelligent surveillance system. In addition, a mesh-type ROI is presented to reduce the lens correction time, so that this independent ROI scheme can parallelize and maximize the processor's utilization.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.1006-1012
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• 2010

For the autonomous navigation of an unmanned ground vehicle in the rough terrain and combat, the dust environment should necessarily be overcome. Therefore, we propose a robust obstacle detection methodology using laser range sensor and radar. Laser range sensor has a good angle and distance accuracy, however, it has a weakness in the dust environment. On the other hand, radar has not better the angle and distance accuracy than laser range sensor, it has a robustness in the dust environment. Using these characteristics of laser range sensor and radar, we use laser range sensor as a main sensor for normal times and radar as a assist sensor for the dust environment. For fusion of laser range sensor and radar information, the angle and distance data of the laser range sensor and radar are separately transformed to the angle and distance data of virtual range sensor which is located in the center of the vehicle. Through distance comparison of laser range sensor and radar in the same angle, the distance data of a fused virtual range sensor are changed to the distance data of the laser range sensor, if the distance of laser range sensor and radar are similar. In the other case, the distance data of the fused virtual range sensor are changed to the distance data of the radar. The suggested methodology is verified by real experiment.