• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.610-616
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• 2012

In this paper, we present a method to detect an object such as ship, rock and buoy from sea IR image for the safety navigation. To this end, we do the image smoothing first and the apply watershed algorithm to segment image into subregions. Since watershed algorithm almost always produces over-segmented regions, it requires posterior merging process to get meaningful segmented regions. We propose an efficient merger algorithm that requires only two times of direct access to the pixels regardless of the number of regions. Also by analyzing IR image obtained from sea environments, we could find out that most horizontal edge come out from object regions. For the given input IR image we extract horizontal edge and eliminate isolated edges produced from background and noises by adopting morphological operator. Among the segmented regions, the regions that have horizontal edges are extracted as final results. Experimental results show the adequacy of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.19-26
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• 2006

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.3
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• pp.355-364
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• 2013

Respect to the input AC voltage and output DC voltage, conventional three-phase PWM rectifier is classified as the voltage type rectifier with boost capability and the current type rectifier voltage with buck capability. Conventional PWM rectifier can not at the same time the boost and buck capability and its bridge is weak in the shoot- through state. These problems can be solved by Z-source PWM rectifier which has all characteristic of voltage and current type PWM rectifier. By shoot-through duty ratio control, the Z-source PWM rectifier can buck and boost at the same time, also, there is no need to consider the dead time. This paper proposes the input AC voltage sensorless control method of a three-phase Z-source PWM rectifier in order to accomplish the unity input power factor and output DC voltage control. The proposed method is estimated the input AC voltage by using input AC current and output DC voltage, hence, the sensor for the input AC voltage detection is no needed. comparison of the estimated and detected input AC voltage, estimated phase angle of the input voltage, the output DC voltage response for reference value, unity power factor, FFT(Fast Fourier Transform) of the estimated voltage and efficiency are verified by PSIM simulation.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.157-163
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• 2013

In this paper, we propose a vision and depth information based real-time hand gesture interface method using finger joint estimation. For this, the areas of left and right hands are segmented after mapping of the visual image and depth information image, and labeling and boundary noise removal is performed. Then, the centroid point and rotation angle of each hand area are calculated. Afterwards, a circle is expanded at following pattern from a centroid point of the hand to detect joint points and end points of the finger by obtaining the midway points of the hand boundary crossing and the hand model is recognized. Experimental results that our method enabled fingertip distinction and recognized various hand gestures fast and accurately. As a result of the experiment on various hand poses with the hidden fingers using both hands, the accuracy showed over 90% and the performance indicated over 25 fps. The proposed method can be used as a without contacts input interface in HCI control, education, and game applications.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.102-107
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• 2011

In this paper, a microfluidic array biochip for simultaneously detecting multiple antigen-antibody bindings was designed and implemented. The biochip has the single channel in which microreaction chambers are serially connected, and the antibody-coated microbeads are packed in each microreaction chamber. In addition, the weir structure was fabricated in the microchannel using the gray-scale photolithography in order to trap the microbeads in the microreaction chamber. Three kinds of antibodies were chosen, and the antibodies were immobilized onto the microbeads by the streptavidin-biotin conjugation. In the experiment, as the fluorescence-labeled antigens were injected into the microchannel, the antigen-antibody bindings were completed in 10 minutes. When the solution with multiple antigens was injected into the microchannel, it was observed that the fluorescence intensity increased in only the corresponding microreaction chambers with few non-specific binding. The microfluidic array biochip implemented in this study provides, even with the consumption of tiny amount of sample and fast reaction time to simultaneously detect multiple immunoreactions.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.190-200
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• 2014

The video-based system of the broadcasters and the video-related institutions have shifted from analogical to digital in worldwide. This migration process can generate a defect, digital dropout, in the quality of the contents. Moreover, there are limited researches focused on these kind of defects and those related have limitations. For that reason, we are proposing a new method for feature extraction emphasizing in the peculiar block pattern of digital dropout based on discrete cosine transform (DCT). For classification of error block, we utilize support vector machine (SVM) which can manage feature vectors efficiently. Further, the proposed method overcome the limitation of the previous one using continuity of frame by frame. It is using only the information of a single frame and works better even in the presence of fast moving objects, without the necessity of specific model or parameter estimation. Therefore, this approach is capable of detecting digital dropout only with minimal complexity.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.291-297
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• 2018

In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.

• Bulletin of the Korean Chemical Society
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• v.34 no.8
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• pp.2425-2430
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• 2013

A simple, fast and robust analytical method was developed to determine imatinib in human plasma using liquid chromatography-tandem mass spectrometry with electrospray ionization in the positive ion mode. Imatinib and labeled internal standard were extracted from plasma with a simple protein precipitation. The chromatographic separation was performed using an isocratic elution of mobile phase involving 5.0 mM ammonium formate in water-5.0 mM ammonium formate in methanol (30:70, v/v) over 3.0 min on reversed-stationary phase. The detection was performed using a triple-quadrupole tandem mass spectrometer in multiple-reaction monitoring mode. The developed method was validated with lower limit of quantification of 10 ng/mL. The calibration curve was linear over 10-2000 ng/mL ($R^2$ > 0.99). The method validation parameters met the acceptance criteria. The spiked samples and standard solutions were stable under conditions for storage and handling. The reliable method was successfully applied to real sample analyses and thus a pharmacokinetic study in 27 healthy Korean male volunteers.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.