• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.825-832
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• 2014

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. Even if some methods have the advantage in low complexity, but they generally suffer form low sensitivity. Also, it is difficult to detect PVC accurately because of the various QRS pattern by person's individual difference. Therefore it is necessary to design an efficient algorithm that classifies PVC based on QRS pattern in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose PVC classification based on QRS pattern using QS interval and R wave amplitude. For this purpose, we detected R wave, RR interval, QRS pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 PVC. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 93.72% in PVC classification.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.410-418
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• 2007

For the purpose of fault detection of the primary control surface, real-time estimation of the longitudinal stability and control derivatives of the DURUMI-II using the flight data is considered in this paper. The DURUM-II, a research UAV developed by KARI, is designed to have split control surfaces for the redundancy and to guarantee safety during the fault mode flight test. For fault mode analysis, the right elevator was deliberately fixed to the specified deflection condition. This study also mentions how to implement the multi-step control input efficiently, and how to switch between the normal mode and the fault mode during the flight test. As a realtime parameter estimation technique, Fourier transform regression method was used and the estimated data was compared with the results of the analytical method and the other available method. The aerodynamic derivatives estimated from the normal mode flight data and the fault mode data are compared and the possibility to detect the elevator fault by monitoring the control derivative estimated in real time by the computer onboard was discussed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.74-76
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• 2010

Digital images or videos are used in modern digital devices. The resolution of HDTV in digital broadcasting system is higher than that of previous analog systems. Also, mobile phone with 3G can provide images as well as video streaming services in realtime. In these circumstances, the visual quality of images has become an important factor. We can make image clear by transient improvement process that reduces transient in edges. In this paper, we present an transient improvement algorithm. The proposed algorithm improves edges by making smooth edge to steep edge. Before performing transient improvement algorithm, edge detection algorithm should be operated. Laplacian operator is used in edge detection, and the absolute value of it is used to calculate gain value. Then, local maximum and minimum values are computed to discriminate current pixel value to raise up or pull down. Compensating value that gain value multiplies with the difference between maximum (or minimum) value and current pixel value adds (or subtracts) to current pixel value. That is, improved signal is generated by making the narrow transient of edge. The advantage of proposed algorithm is that it doesn't produce shooting problem like overshoot or undershoot.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.1
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• pp.47-60
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• 2006

Due to the uneven illumination of FPD panel surface, it is difficult to detect the defects. The paper proposes a method to find the uneven illumination compensation using wavelets, which are done based on multi-resolution structure. The first step is to decompose the image into multi-resolution levels. Second, elimination of lowest smooth sub-image with highest frequency band removes the high frequency noise and low varying illumination. In particular, the main algorithm was implemented by lifting scheme for realtime inline process.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.465-470
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• 2010

This paper proposes an adaptive video watermarking algorithm according to bit detection rate of watermark in MPEG2 system. The watermark strength is adaptively applied as BER(bit error rate) of watermark extracted from decoded frame for motion compensation. Watermark insertion uses a frequency spread spectrum method. A realtime watermark extraction is done directly in the DCT domain during MPEG decoding. The experimental simulations show that PSNR(peak signal to noise ratio) results 31.5dB for a fixed watermark strength and 33.dB for an adaptive watermark strength. Also average BER is 0.126 and less than 0.2 avaliable value.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.219-222
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• 2023

Partial discharges (PD) have long been recognized as a major contributing factor to catastrophic failures in high-power equipment. As the demand for high voltage direct current (HVDC) facilities continues to rise, the significance of on-line and real-time monitoring of PD becomes increasingly prominent. In this study, we have designed, fabricated, and characterized a highly sensitive and cost-effective PD sensor comprising a pair of copper electrodes with different arc lengths. The key advantage of our sensor is its non-invasive nature, as it can be installed at any location along the entire power cable without requiring structural modifications. In contrast, conventional PD sensors are typically limited to installation at cable terminals or insulation joint boxes, often necessitating invasive alterations. Our PD sensor demonstrates exceptional accuracy in estimating PD location, with a success rate exceeding 95% in the straight sections of the power cable and surpassing 89% in curved sections. These remarkable characteristics indicate its high potential for realtime and on-line detection of PD.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.11-21
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• 2011

An embedded sensor is significantly influenced by its spatial environment, such as barriers or distance, through low power and signal strength. Due to these causes, noise data frequently occur in an embedded sensor. Because the information acquired from the embedded sensor exists in a time series, it is hard to detect an error which continuously takes place in the time series information on a realtime basis. In this paper, we proposes an error detection method based on time-series prediction that detects error signals of embedded sensors in real time in consideration of the physical characteristics of embedded devices. The error detection method based on time-series prediction proposed in this paper determines errors in generated embedded device signals using a stable distance function. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.462-470
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• 2011

We proposed a realtime object tracking system that detects the abandoned or disappeared objects. Because these events are caused by human, we used the tracking based algorithm. After the background subtraction by Gaussian mixture model, the shadow removal is applied for accurate object detection. The static object is classified as either of abandoned objects or disappeared object. We assigned monitoring time to the static object to overcome a situation that it is being overlapped by other object. We obtained more accurate detection by using region growing method. We implemented our algorithm by DSP processor and obtained an excellent result throughout the experiment.

• Nuclear Engineering and Technology
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• v.39 no.5
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• pp.637-646
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• 2007

An UET (ultrasound excited thermography) has been used for several years for a remote non-destructive testing in the automotive and aircraft industry. It provides a thermo sonic image for a defect detection. A thermograhy is based On a propagation and a reflection of a thermal wave, which is launched from the surface into the inspected sample by an absorption of a modulated radiation. For an energy deposition to a sample, the UET uses an ultrasound excited vibration energy as an internal heat source. In this paper the applicability of the UET for a realtime defect detection is described. Measurements were performed on two kinds of pipes made from a copper and a CFRP material. In the interior of the CFRP pipe (70mm diameter), a groove (width - 6mm, depth - 2.7mm, and length - 70mm) was engraved by a milling. In the case of the copper pipe, a defect was made with a groove (width - 2mm, depth - 1mm, and length - 110 mm) by the same method. An ultrasonic vibration energy of a pulsed type is injected into the exterior side of the pipe. A hot spot, which is a small area around the defect was considerably heated up when compared to the other intact areas, was observed. A test On a damaged copper pipe produced a thermo sonic image, which was an excellent image contrast when compared to a CFRP pipe. Test on a CFRP pipe with a subsurface defect revealed a thermo sonic image at the groove position which was a relatively weak contrast.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.24-32
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• 2010

In this paper we proposed an object tracking system that detects the abandoned and removed objects, which is to be used in the intelligent surveillance applications. After the GMM based background subtraction and by using histogram method, the static region is identified to detect abandoned and removed objects. Since the system is implemented on DSP chip, it operates in realtime and is programmable. The input videos used in the experiment contain various indoor and outdoor scenes, and they are categorized into three different complexities; low, midium and high. By 10 times of experiment, we obtained high detection ratio at low and medium complexity sequences. On the high complexity video, successful detection ratio was relatively low because the scene contains crowdedness and repeated occlusion. In the future work, these complicated situation should be solved.