• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.29-36
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• 2008

In this paper we propose a real-time method to estimate a pointing region from two camera images. In general, a pointing target exists in the face direction when a human points to something. Therefore, we regard the direction of pointing as the straight line that connects the face position with the fingertip position. First, the method extracts two points in the face and the fingertips region by using detecting the skin color of human being. And we used the 3D geometric information to obtain a pointing detection and its region. In order to evaluate the performance, we have build up an ICIGS(Interactive Cinema Information Guiding System) with two camera and a beam project.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.420-420
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• 2014

최근, 과학 기술이 발달함에 따라 현장에서의 실시간 검사 및 자가 지단 등 질병 치유에 대한 사람들의 관심이 증가하고 있으며, 이에 따라 의료, 환경, 산업과 같은 많은 분야에서 바이오 센서에 대한 연구가 활발하게 이루어지고 있다. 그 중, EGFET는 전해질 속의 각종 이온 농도를 전기적으로 측정하는 바이오 센서로, 외부 환경으로부터 안전하고, 제작이 쉬우며, 재활용이 가능하여 비용을 절감 할 수 있다는 장점을 가지고 있다 [1]. EGFET는 감지부와 FET부로 분리된 구조를 가지고 있으며, 감지부의 감지막으로는 Al2O3, HfO2, $TiO_2$, SnO2 와 같은 다양한 물질들이 사용되고 있다. 그 중, SnO2는 우수한 감도와 안정성을 가지고 있는 물질로 추가적인 열처리 공정 없이도 우수한 감지 특성을 나타내기 때문에 본 연구에서 감지막으로 사용하였다. 한편, EGFETs 의 FET부로는 기존의 비정질 실리콘 TFTs 에 비해 10배 이상의 높은 이동도와 온/오프 전류비를 갖는 InGaZnO 를 채널층으로 사용한 TFTs 를 사용하였다. a-IGZO 는 넓은 밴드 갭으로 인해 가시광 영역에서 투명하며, 향후 투명 바이오센서 제작 시, 물질들 사이의 반응을 전기적 신호뿐만 아니라 광학적인 분석 방법으로도 검출이 가능하기에 고 신뢰성을 갖는 센서의 제작이 가능할 것으로 기대된다. 한편, a-IGZO TFTs 의 경우 우수한 전기적 특성을 나타냄에도 불구하고 소자 동작 시 문턱 전압이 불안정하다는 단점이 있으며 [2], 이러한 문제의 개선과 향후 투명 기판 위에서의 소자 제작을 위해서는 저온 열처리 공정이 필수적이다. 따라서, 본 연구에서는 저온 열처리 공정인 u-wave 열처리를 통하여 a-IGZO TFTs 의 전기적 특성 및 안정성을 향상시켰으며, 9.51 [$cm2/V{\cdot}s$]의 이동도와 135 [mV/dec] 의 SS값, 0.99 [V]의 문턱 전압, 1.18E+08의 온/오프 전류 비를 갖는 고성능 스위칭 TFTs 를 제작하였다. 최종적으로, 제작된 a-IGZO TFTs 를 SnO2 감지막을 갖는 EGFETs 에 적용함으로써 우수한 감지 특성과 안정성을 갖는 바이오 센서를 제작하였다.

• Analytical Science and Technology
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• v.15 no.5
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• pp.482-487
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• 2002

International Olympic Committee (IOC) prohibits the use of carteolol which is one of ${\beta}$-blockers. To prove whether carteolol product was taken or not, the analytical method in urine using GC/MS was established, and metabolism and excretion study were evaluated. As compared with acid hydrolysis, enzyme hydrolysis method was more efficiency. Coefficients of variation for intra-assay precision was around 10%. Error was less than 5% except the concentration of $0.05{\mu}g/m{\ell}$. Recovery was 78.5% at $2{\mu}g/m{\ell}$. Free carteolol, conjugated carteolol, and small amount of p-OH carteolol were found in dosed human urine samples. The conjugated form was being 59.4% of the total carteolol in human urine. The amount of carteolol renal excreted for 72 h after oral dose of 10 mg of carteolol was 49% of the administred dose.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.178-184
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• 2007

The EEG signal in general can be categorized as the Alpha wave, the Beta wave, the Theta wave, and the Delta wave. The alpha wave, showed in stable state, is the dominant wave for a human EEG and the beta wave displays the excited state. The subject of this paper was to recognize the stable state of EEG quantitatively using wavelet transform and power spectrum analysis. We decomposed EEG signal into the alpha wave and the beta wave in the process of wavelet transform, and calculated each power spectrum of EEG signal, using Fast Fourier Transform. And then we calculated the stable state quantitatively by stable state ratio, defined as the power spectrum of the alpha wave over that of the beta wave. The study showed that it took more than 10 minutes to reach the stable state from the normal activity in 69 % of the subjects, 5 -10 minutes in 9%, and less than 5 minutes in 16 %.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.161-166
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• 2011

In this paper, we propose a novel background segmentation and feature point extraction method of a human motion for the augmented reality game. First, our method transforms input image from RGB color space to HSV color space, then segments a skin colored area using double threshold of H, S value. And it also segments a moving area using the time difference images and then removes the noise of the area using the Hessian affine region detector. The skin colored area with the moving area is segmented as a human motion. Next, the feature points for the human motion are extracted by calculating the center point for each block in the previously obtained image. The experiments on various input images show that our method is capable of correct background segmentation and feature points extraction 12 frames per second.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.945-951
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• 2007

Noise cancellation is essential for the devices which use speech as an interface. In real environments, speech quality and recognition rates are degraded by the auditive noises coming near the microphone. In this paper, we propose a noise cancellation algorithm using stereo microphones basically. The advantage of the use of multiple microphones is that the direction information of the target source could be applied. The proposed noise canceller is based on the Wiener filter. To estimate the filter, noise and target speech frequency responses should be known and they are estimated by the spectral classification in the frequency domain. The performance of the proposed algorithm is compared with that of the well-known Frost algorithm and the generalized sidelobe canceller (GSC) with an adaptation mode controller (AMC). As performance measures, the perceptual evaluation of speech quality (PESQ), which is the most widely used among various objective speech quality methods, and speech recognition rates are adopted.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.3029-3034
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• 2014

The paper describes the scleral diagnostic system implementation for human eyes by using the scleral color code and vessels sign pattern code generations. The system is based on the high performance DSP image signal processor, programmable gain control for preprocessing and RISC SD frames storage. RGB image signals are optimized by PGC, the edge image is detected form the gray image converted. The processing algorithms are executed by scleral color code generation and scleral vessels sign pattern code creation for discriminating and matching. The scleral symptomatic color code is generated by YCbCr values at memory map tolerated and the vessel sign pattern code is created by digitizing the 24 clock and 13 ring zones, overlay matching and tolerances. The experimental results for performance are that the system runs 40ms, and the color and pattern for diagnostic errors are around 20% and 24% on average. The system and technique enable a scleral diagnosis with subdividing the patterns and patient database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1049-1054
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• 2018

Keyword searching used in the past as a method of finding similar patents, and automated classification by machine learning is using in recently. Keyword searching is a method of analyzing data that is formalized through data refinement. While the accuracy for short text is high, long one consisted of several words like as document that is not able to analyze the meaning contained in sentences. In semantic analysis level, the method of automatic classification is used to classify sentences composed of several words by unstructured data analysis. There was an attempt to find similar documents by combining the two methods. However, it have a problem in the algorithm w the methods of analysis are different ways to use simultaneous unstructured data and regular data. In this paper, we study the method of extracting keywords implied in the document and using the LDA(Latent Semantic Analysis) method to classify documents efficiently without human intervention and finding similar patents.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.70-81
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• 2001

This paper presents a 3D face modeling method using a CCD camera and a projector (LCD projector or Slide projector). The camera faces the human face and the projector casts white stripe patterns on the human face. The 3D shape of the face is extracted from spatial and temporal locations of the white stripe patterns on a series of image frames. The proposed method employs region segmentation and multi-beam techniques for efficient 3D modeling of hair region and faster 3D scanning respectively. In the proposed method, each image is segmented into face, hair, and shadow regions, which are independently processed to obtain the optimum results for each region. The multi-beam method， which uses a number of equally spaced stripe patterns, reduces the total number of image frames and consequently the overall data acquisition time. Light beam calibration is adopted for efficient light plane measurement, which is not influenced by the direction (vertical or horizontal) of the stripe patterns. Experimental results show that the proposed method provides a favorable 3D face modeling results, including the hair region.

• Korean Journal of Optics and Photonics
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• v.17 no.2
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• pp.113-119
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• 2006

We need a good image of the retina of the human eye in order to inspect or cure it. In this work, an optical system design for a retinal camera is studied and the finite schematic eye model made by Sang Gee Kim and Sung Chan Park is used. The optical system is composed of four lens groups. The rays of the entire object field are collected on the center by the 1st group and the objective is imaged by all the other groups. The image is detected by the CCD array and displayed by a monitor The 1st lens group is employed singlet and other groups are employed triplets. Ray aberrations, spot diagrams, diffraction line spread functions and MTFs are calculated for optical performance assessment. This design may be very useful for the development of a retinal camera with high performance.