• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2118-2125
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• 2014

Gait Recognition is a new technique to identify the people by the way they walk. Human gait is a spatio-temporal phenomenon that typifies the motion characteristics of an individual. The proposed method makes a simple but efficient attempt to gait recognition. For each video file, spatial silhouettes of a walker are extracted by an improved background subtraction procedure using Gaussian Mixture Model (GMM). Here GMM is used as a parametric probability density function represented as a weighted sum of Gaussian component densities. Then, the relevant features are extracted from the silhouette tracked from the given video file using the Principal Component Analysis (PCA) method. The Fisher Linear Discriminant Analysis (FLDA) classifier is used in the classification of dimensional reduced image derived by the PCA method for gait recognition. Although gait images can be easily acquired, the gait recognition is affected by clothes, shoes, carrying status and specific physical condition of an individual. To overcome this problem, it is combined with footprint as a multimodal biometric system. The minutiae is extracted from the footprint and then fused with silhouette image using the Discrete Stationary Wavelet Transform (DSWT). The experimental result shows that the efficiency of proposed fusion algorithm works well and attains better result while comparing with other fusion schemes.

• Journal of Korean Neurosurgical Society
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• 제40권4호
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• pp.277-280
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• 2006

Extracerebral cavernous hemangiomas are rare vascular tumors that are very difficult to remove because of severe intraoperative bleeding. We report a case of 57-year-old male with extracerebral cavernous hemangioma with review of 126 cases in the literature. Patient presented with blurred vision, diplopia, numbness on the left side of his face. Magnetic resonance imaging revealed a well defined mass of $3{\times}4{\times}3cm$ size with heterogenous iso-or hypointensity on T1-weighted image showing strong homogenous contrast enhancement and marked hyperintensity on T2-weighted image. Digital subtraction angiography[DSA] revealed a faint tumor blush by feeders from the left internal carotid artery[ICA] and left external carotid artery[ECA] in the delayed phase. Even with profuse intratumoral bleeding, near total removal was achieved. In addition to preoperative neurologic deficits such as ophthalmoplegia, facial numbness in the V1-2 dermatomes, ptosis appeared postoperatively.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.414-417
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• 1997

This paper presents vessel contour for extracting features and segmentating narrow blood vessels down to a diameter of two pixels in digital subtraction angiographic image. We present a new tracking algorithm for contour, mainly blood vessels in DSA image, and extracting properties such as their intensities, diameters, and center lines by exploiting spatial continuity. The proposed algorithm comes to detect blood vessel's boundary using difference edge detector one of homogeneity operator and find a next centerline position by direction vector of edge information. This algorithm enhanced variation of vessel's diameter compared to Sun's tracking algorithm and lessoned to compute as direction vector decide adaptively entire vessel's direction field. The processed images are intended to support radiologists in diagnosis, radiation therapy planning, and surgical planning. The algorithm should be useful for automating angiographic analyses of blood vessels.

• 한국CDE학회논문집
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• 제19권2호
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• pp.111-118
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• 2014

In tangible augmented reality (AR) environments, the user interacts with virtual objects by manipulating their physical counterparts, but he or she often encounters awkward situations in which his or her hands are occluded by the augmented virtual objects, which causes great difficulty in figuring out hand positions, and reduces both immersion and ease of interaction. To solve the problem of such hand occlusion, skin color information has been usefully exploited. In this paper, we propose an approach to simple and effective construction of a skin color map which is suitable for hand segmentation and tangible AR interaction. The basic idea used herein is to obtain hand images used in a target AR environment by simple image subtraction and to represent their color information by a convex polygonal map in the YCbCr color space. We experimentally found that the convex polygonal map is more accurate in representing skin color than a conventional rectangular map. After implementing a solution for resolving hand occlusion using the proposed skin color map construction, we showed its usefulness by applying it to virtual design evaluation of digital handheld products in a tangible AR environment.

• 대한임베디드공학회논문지
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• 제14권6호
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• pp.295-311
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• 2019

The smart product market is growing year by year and is being used in many areas. There are various ways of interacting with smart products and users by inputting voice recognition, touch and finger movements. It is most important to detect an accurate hand region as a whole step to recognize hand movement. In this paper, we propose a method to detect accurate hand region in real time in various environments. A conventional method of detecting a hand region includes a method using depth information of a multi-sensor camera, a method of detecting a hand through machine learning, and a method of detecting a hand region using a color model. Among these methods, a method using a multi-sensor camera or a method using a machine learning requires a large amount of calculation and a high-performance PC is essential. Many computations are not suitable for embedded systems, and high-end PCs increase or decrease the price of smart products. The algorithm proposed in this paper detects the hand region using the color model, corrects the problems of the existing hand detection algorithm, and detects the accurate hand region based on various experimental environments.

• 대한임베디드공학회논문지
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• 제10권6호
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• pp.363-372
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• 2015

Recent some SoC FPGA Releases that integrate ARM processor and FPGA fabric show better performance compared to the ASIC SoC used in typical embedded image processing system. In this study, using the above advantages, we implement a SoC FPGA-based Real-Time Object Recognition and Tracking System. In our system, the video input and output, image preprocessing process, and background subtraction processing were implemented in FPGA logics. And the object recognition and tracking processes were implemented in ARM processor-based programs. Our system provides the processing performance of 5.3 fps for the SVGA video input. This is about 79 times faster processing power than software approach based on the Nios II Soft-core processor, and about 4 times faster than approach based the HPS processor. Consequently, if the object recognition and tracking system takes a design structure combined with the FPGA logic and HPS processor-based processes of recent SoC FPGA Releases, then the real-time processing is possible because the processing speed is improved than the system that be handled only by the software approach.

• 치과방사선
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• 제23권1호
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• pp.125-136
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• 1993

The geometrically standardized intraoral radiographs using 5 occlusal registration materials were taken serially from immediate, 1 day, 2, 4, 8, 12, and 16 weeks after making the bite blocks. And the resultant images were digitally subtracted using the immediately taken film as reference images. The qualities of those subtracted images were evaluated to check the degree of reproducibility of each impression material. The results were as follows: 1. The standard deviations of the grey scales of the overall subtracted images were 4.9 for Exal1ex, 7.2 for Pattern resin, 9.0 for Tooth Shade Acrylic, 12.2 for XCP only, 14.8 for Impregum. the lesser the standard deviation, the better the quality of the subtracted images. 2. The standard deviation of the grey scales of the overall subtracted images were grossly related to those of the localized horizontal line of interest. 3. Exaflex which showed the best subtracted image quality had 15 cases of straight, 14 cases of wave, 1 case of canyon shape. Impregum which showed the worst subtracted image quality had 4 cases of straight, 8 cases of wave, 18 cases of canyon shape respectively.

• 대한전자공학회논문지SP
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• 제37권3호
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• pp.31-40
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• 2000

영상정보에 기반한 교통제어시스템의 핵심요소인 교통영상에서의 차량의 위치, 대수를 측정하는 견실한 기법을 제시하였다. 제안한 기법은, 배경영상을 제거한 차 영상으로부터 국부 최적 임계값 산출기법에 의해 차량의 밝고 어두운 증거영역을 추출하고 차량의 기하학적 특정을 이용해 3개의 규칙으로 합병하는 증거추론 (Evidential reasoning)에 기반을 두었다 국부 최적 임계값 산출기법은 차량형상이 중첩되었거나 차량의 색상이 배경영상과 유사할 경우에도 치량의 밝고 어두운 증거영역의 분리를 보장한다 다양한 교통영상에 적용한 결과 카메라의 거리, 위치, 날씨 등의 동작 환경의 변화에 매우 견실한 검지 성능을 가점을 확인하였고 프레임사이의 움직임 정보를 사용하지 않았으므로 차량의 흐름이 정체되었을 경우에도 적용이 가능하다.

• 전자공학회논문지SC
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• 제40권2호
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• pp.26-37
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• 2003

치과의사는 일반 의사들과 다르게 진단과 치료를 위한 거의 모든 과정을 혼자서 처리하는 것이 일반적이다. 이러한 환경에서 치과의사의 진단효율을 향상시키기 위해서는 진단자료와 방사선사진이 동시에 제시되는 효율적인 진료환경이 필요하다. 본 논문에서는 치과병원에서의 진단과 치료를 위한 통합환경을 제안한다 제안된 시스템은 치과병원의 주요업무인 환자기록생성, 진단을 위한 영상취득과 분석, 치료계획수립, 시술시뮬레이션 등을 하나의 시스템으로 유기적으로 결합함으로서 필름과 종이가 없는 병원환경을 실현하였다. 또한 모든 임상자료의 신속한 검색과 정량적인 분석을 지원함으로서 환자에게 보다 정확하고 예측이 가능한 치료를 제공할 수 있도록 하였다.

• 한국정보통신학회논문지
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• 제10권2호
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• pp.308-314
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• 2006

수 마이크로 단위로 계측되는 반도체 COG의 검사 정밀도를 높이기 위해서 라인스캔 카메라가 이용된다. 여러 가지 불량 요인 중 이물질 검출은 COG 패턴이 미세하고 복잡하기 때문에 불량 자동 검사 단계에서 가장 어려운 기술이었다. 본 논문에서는 매칭 속도를 높이기 위하여 2단계 영역분할 템플릿 매칭 방법을 제안하였다. 아울러 수 마이크로 단위의 이물짙 검출을 위하여 그라디언트 마스크와 AND 연산을 이용한 새로운 방법을 제안하였다. 제안된 2단계 템플릿 매칭을 사용한 방법은 기존의 상관 계수 이용법 에 비해 0.3-0.4초 매칭 속도를 향상시켰다. 그리고 제안된 마스크 적용 이물질 검출방법은 기존 마스크를 이용하지 않은 방법에 비해 불량 검출률을 $5-8\%$ 향상시켰다.