• 한국전기전자재료학회논문지
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• 제25권1호
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• pp.53-57
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• 2012

In this paper, by designing 20 W class driving circuit for driving high-power LED (Light Emitting Diode), we are going to comparatively carry out the analysis of characteristics for power circuit according to each design method. In this case, 200 V 60 Hz was performed as input data. The electrical characteristics such as voltage, current and ripple are checked for constant current circuit and constant voltage circuit in the LED module. In addition, as the ripple has an influence on illumination of LED light, low temperature working (-20 [$^{\circ}C$]) and high temperature working(80 [$^{\circ}C$]) are measured to make sure the ripple characteristics in accordance with temperature. In low temperature operation -20 [$^{\circ}C$] measurements, both constant current circuit and constant-voltage circuit were less impacted on input fluctuation, whereas in the high temperature operation 80 [$^{\circ}C$], current voltage in constant voltage circuit was surge after 430 [hour]. Voltage current ripple of constant current circuit was much less than constant voltage circuit, therefore we can show that constant current circuit is more stable.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1398-1400
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• 1996

In this paper, a method of the decision of the road direction for ALV(Autonomous Land Vehicle) road following by region-based segmentation is presented. The decision of the road direction requires extracting road regions from images in real-time to guide the navigation of ALV on the roadway. Two thresholds to discriminate between road and non-road region in the image are easily decided, using knowledge of problem region and polygonal approximation that searches multiple peaks and valleys in histogram of a road image. The most likely road region of the binary image is selected from original image by these steps. The location of a vanishing point to indicate the direction of the road can be obtained applying it to X-Y profile of the binary road region again. It can successfully steer a ALV along a road reliably, even in the presence of fluctuation of illumination condition, bad road surface condition such as hidden boundaries, shadows, road patches, dirt and water stains, and unusual road condition. Pyramid structure also saves time in processing road images and a real-time image processing for achieving navigation of ALV is implemented. The efficacy of this approach is demonstrated using several real-world road images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.