• 한국전자파학회논문지
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• 제16권10호
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• pp.965-972
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• 2005

본 연구에서는 DTV, HDTV 서비스를 동시에 제공하는 차세대 위성 방송시스템의 표준안인 DVB-S2에서 채널 부호화 알고리즘으로 채택한 LDPC 부호의 복호 알고리즘에 대해 연구를 하였다. 샤논의 한계에 근접하기 위해서는 큰 블록 사이즈의 LDPC 부호어 길이와 많은 반복 횟수를 요구한다. 이는 많은 계산량을 요구하며, 그리고 이에 따른 전력 소비량(power consumption)을 야기시키므로 본 논문에서는 세 가지 형태의 low complexity LDPC 복호 알고리즘을 제시한다. 첫째로 큰 블록 사이즈와 많은 반복 회수는 많은 계산량과 power 소모량을 요구하므로 성능 손실 없이 반복 횟수를 줄일 수 있는 SUBSET 방법을 이용한 복호 알고리즘, 둘째로 early stop 알고리즘에 대해 연구하였고, 셋째로 비트 노드 계산과 체크 노드 계산시 일정한 신뢰도 값보다 크면 다음 반복시 계산을 하지 않는 early detection 알고리즘에 대해 연구하였다.

• 한국통신학회논문지
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• 제35권2C호
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• pp.148-154
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• 2010

본 연구에서는 무선 랜 표준안인 802.11n에서 채널 부호화 알고리즘으로 채택된 LDPC부호의 복호 알고리즘의 저복잡도에 대해 연구를 하였다. 샤논의 한계에 근접하기 위해서는 큰 블록 사이즈의 LDPC 부호어 길이와 많은 반복횟수를 요구한다. 이는 많은 계산량을 요구하며, 그리고 이에 따른 전력 소비량(power consumption)을 야기시키므로 본 논문에서는 세 가지 형태의 저복잡도 LDPC 복호 알고리즘을 제시한다. 첫째로 큰 블록 사이즈와 많은 반복 횟수는 많은 계산량과 전력 소모량을 요구하므로 성능 손실 없이 반복횟수를 줄일 수 있는 부분 병렬 방법을 이용한 복호 알고리즘, 둘째로 early stop 알고리즘에 대해 연구 하였고, 셋째로 비트 노드 계산과 체크 노드 계산 시 일정한 신뢰도 값보다 크면 다음 반복 시 계산을 하지 않는 early detection 알고리즘에 대해 연구 하였다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제12권2호
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• pp.150-161
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• 2012

Eye detection is widely used in applications, such as face recognition, driver behavior analysis, and human-computer interaction. However, it is difficult to achieve real-time performance with software-based eye detection in an embedded environment. In this paper, we propose a parallel hardware architecture for real-time eye detection. We use the AdaBoost algorithm with modified census transform(MCT) to detect eyes on a face image. We parallelize part of the algorithm to speed up processing. Several downscaled pyramid images of the eye candidate region are generated in parallel using the input face image. We can detect the left and the right eye simultaneously using these downscaled images. The sequential data processing bottleneck caused by repetitive operation is removed by employing a pipelined parallel architecture. The proposed architecture is designed using Verilog HDL and implemented on a Virtex-5 FPGA for prototyping and evaluation. The proposed system can detect eyes within 0.15 ms in a VGA image.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권5호
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• pp.557-563
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• 2016

Most of the existing hand detection methods rely on the contour shape of hand after skin color segmentation. Such contour shape based computations, however, are not only susceptible to noise and other skin color segments but also inherently sequential and difficult to efficiently parallelize. In this paper, we implement and accelerate our in-house distance image based approach using CPU-GPU heterogeneous computing. Using emerging CPU-GPU heterogeneous computing technology, we achieved 5.0 times speed-up for $320{\times}240$ images, and 17.5 times for $640{\times}480$ images and our experiment demonstrates that our proposed distance image based hand detection is robust and fast, reaching up to 97.32% palm detection rate, 80.4% of which have more than 3 fingers detected on commodity processors.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• Advances in pediatric surgery
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• 제10권2호
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• pp.131-135
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• 2004

The purpose of this retrospective study was to evaluate the effects of diagnostic sonography in pediatric patients with inguinal hernias. The patients were classified into two groups. Group A included the patients who had been operated upon for inguinal hernia in 1980's, when diagnostic sonography was not available. Group B included the patients, operated upon for inguinal hernia from 2001 to 2002, when inguinal sonography was employed to detect potential bilateral hernias. The age distribution, sex ratio, laterality, bilaterality, and concomitant symptoms were compared between group A and group B. There were 296 cases in group A and 377 cases in group B. The prevalent age group was from 1 to 5 years. There was no difference in age group distribution between both groups. The male to female ratio was 5.3:1 in group A and 3.5:1 in group B. The ratio of unilateral to bilateral hernia was 5:1 in group A and 3:1 in group B. In cases with a unilateral hernia, the ratio of right to left was 1.5:1 in group A and 1.8:1 in group B. In cases with bilateral hernia, the simultaneous bilateral hernia was 33 cases (67.4 %) in group A and 75 cases (80.6 %) in group B. The sequential bilateral hernia was 16 cases (32.7 %) in group A and 18 cases (19.4 %) in group B. Although the ratio of bilateral hernia was increased in group B, the portion of the sequential bilateral hernia was significantly decreased in group B. In conclusion, there were no differences in the age distribution and the laterality between group A and B. The ratio of female patients and the incidence of bilateral hernia were increased in group B even though the portion of the sequential bilateral hernia was decreased. This result shows that the preoperative inguinal sonography in unilateral hernia with potential bilateral hernia is useful in early detection of the sequential contralateral hernia.

• Journal of Yeungnam Medical Science
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• 제16권1호
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• pp.101-107
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• 1999

휴식 Tl-201/부하 Tc-99m MIBI 심근관류 SPECT를 흉통을 주소로 내원한 24명의 환자를 대상으로 시행하고, 관상동맥조영술에서 관상동액의 내경이 50%이상 협착이 있는 경우를 유의한 것으로 보고 SPECT결과와 관상동맥조영술의 결과를 비교하였다. 관상동맥질환 진단의 민감도와 특이도는 모두 91.7%였고, 협착이 있는 관상동맥 분지수에 따른 민감도는 단일혈관질환이 75%, 다중혈관질환이 100% 였다. 관상동맥분지 각각에 대한 전단의 민감도는 좌전하행동맥 78%, 좌회선동맥 80%, 우관상동맥 86%였다. 이 연구의 절과와 기존의 Tl-201 이나 Tc-99m MIBI를 단독으로 사용한 경우와 비교했을 때 관상동맥질환 진단의 민감도와 특이도는 비슷하거나 오히려 더 좋은 결과를 보였다. 또한 이 방법은 진정한 의미의 휴식기영상을 얻을 수 있고 휴식기와 부하기 영상 사이에 남아있는 방사능으로 인한 오차에서 벗어날 수 있으며, 휴식기 촬영 후 바로 부하기 촬영을 하므로 전체 검사시간이 줄어 환자에게 편리하고 효율이 높은 검사법이라 생각된다.

• 한국멀티미디어학회논문지
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• 제8권1호
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• pp.1-8
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• 2005

유사 멜로디 검색은 질의 멜로디와 유사한 멜로디들을 음악 데이터베이스로부터 찾는 연산이다. 본 논문에서는 유사 멜로디 검색을 기반으로 하는 표절 감지 시스템 개발에 관하여 논의한다. 먼저, 정합 및 이동 변환을 지원하는 새로운 유사 모델을 제안한다. 또한, 각 멜로디 의 특징들을 인덱싱 하는 방법과 인덱스를 기반으로 표절 감지를 처리하는 방법을 제시한다 제안된 표절 감지 시스템을 이용하여 작곡가는 자신의 멜로디와 유사한 멜로디를 가지 는 곡들을 음악 데이터베이스에서 효과적으로 검색할 수 있다. 실험 을 통한 성능평가를 통하여 제안된 기법의 우수성을 규명한다. 실험 결과에 의하면, 제안된 기법은 순차 검색을 기반으로 하는 방법과 비교하여 약 31배까지의 성능 개선 효과를 보였다.

• 제어로봇시스템학회논문지
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• 제21권9호
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• pp.858-862
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• 2015

This paper presents a new forward-viewing mono-camera based obstacle detection algorithm for mobile robots. The proposed method extracts the coarse location of an obstacle in an image using inverse perspective mapping technique from sequential images. In the next step, graph-cut based image labeling is conducted for estimating the exact obstacle boundary. The graph-cut based labeling algorithm labels the image pixels as either obstacle or floor as the final outcome. Experiments are performed to verify the obstacle detection performance of the developed algorithm in several examples, including a book, box, towel, and flower pot. The low illumination condition, low color contrast between floor and obstacle, and floor pattern cases are also tested.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.175-177
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• 1995

The sensor signal validation and failure detection system must be able to detect, isolate, and identify sensor degradation as well as provide a reconstruction of the measurements. In this study, this is accomplished by combining the neural network, the Generalized Consistency Checking(GCC), and the Sequential Probability Ratio Test(SPRT) method in a decision estimator module. The GCC method is a computationally efficient system for redundant sensors, while the SPRT provides the ability to make decisions based on the degradation history of a sensor. The methodology is also extended to the detection of noise degradation. The acceptability of the proposed method is demonstration by using the simulation data in safety injection accident of nuclear power plants. The results show that the signal validation and sensor failure detection system is able to detect and isolate a bias failure and noise type failures under transient conditions. And also, the system is able to provide the validated signal by reconstructing the measurement signals in the failure conditions considered.