• Title/Summary/Keyword: 문제영역 검출

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Time-Stamp based Locking scheme for Update Spatial Data of Wireless Mobile Client (무선 이동 클라이언트에서 공간 데이터 변경을 위한 타임스탬프 기반 잠금 기법)

  • 이주형;김동현;홍봉희
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.37-39
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    • 2001
  • 현재 이동 클라이언트의 발전과 무선 이동 데이터 통신의 발달에 의해 보다 정학한 공간 데이터 수정을 현장에서 수행 할 수 있게 되었다. 이러한 환경을 고려하여, 이 논문에서는 무선 이동 클라언트에서의 공간데이터 변경을 위해서 2-tier 트랜잭션 모델(2)을 이용한다. 이동 트랜잭션은 완료 즉시 서버에 재 접속할 필요가 없기 때문에 이동 트랜잭션의 완료 시점과 재 접속 후 베이스 트랜잭션으로 재 수행하는 시점 사이에 간격이 존재하게 된다. 그리고 고안 데이터 변경 트랜잭션은 교환가능한 트랜잭션이 아니며, 완전히 직렬가능(fully serializerability)해야 한다. 이러한 이유로 갱신 손실 문제(lost update problem)가 발생한다. 이 논문에서는 갱신 손실 문제를 해결하기 위하여 영역 잠금의 타입스탬프 값과 영역 잠금의 영역의 겹침을 이용하여 갱신 손실 가능한 공간객체 집합을 검출해내는 방법을 제시한다. 검출된 갱신 손실 가능한 공간 객체 집합의 완료 시점을 뒤로 연기(postpone)하는 프로토콜도 함께 제시한다.

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Tooth Region Segmentation by Oral Cavity Model and Watershed Algorithm (구강구조모델과 워터쉐드를 이용한 치아영역 분할)

  • Na, S.D.;Lee, G.H.;Lee, J.H.;Kim, M.N.
    • Journal of Korea Multimedia Society
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    • v.16 no.10
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    • pp.1135-1146
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    • 2013
  • In this paper, we proposed a new algorithm for individual tooth region segmentation on tooth color images. The proposed algorithm used oral cavity model based on structural feature of tooth and new boundary of watershed algorithm. First, the gray scale image is obtained with emphasized tooth regions from the color images and unnecessary regions are removed on tooth images. Next, the image enhancement of tooth images is implemented using the proposed oral cavity model, and the individual tooth regions are segmented by watershed algorithm on the enhanced images. Boundary and seeds necessary to watershed algorithm are applied boundary of binary image using minimum thresholding and region maximum value. In order to evaluate performance of proposed algorithm, we conduct experiment to compare conventional algorithm with proposed algorithm. As a result of experiment, we confirmed that the proposed algorithm is more improved detection ratio than conventional algorithm at molar regions and the tooth region detection performance is improved by preventing overlap detection on oral cavity.

Real Time Lip Reading System Implementation in Embedded Environment (임베디드 환경에서의 실시간 립리딩 시스템 구현)

  • Kim, Young-Un;Kang, Sun-Kyung;Jung, Sung-Tae
    • The KIPS Transactions:PartB
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    • v.17B no.3
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    • pp.227-232
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    • 2010
  • This paper proposes the real time lip reading method in the embedded environment. The embedded environment has the limited sources to use compared to existing PC environment, so it is hard to drive the lip reading system with existing PC environment in the embedded environment in real time. To solve the problem, this paper suggests detection methods of lip region, feature extraction of lips, and awareness methods of phonetic words suitable to the embedded environment. First, it detects the face region by using face color information to find out the accurate lip region and then detects the exact lip region by finding the position of both eyes from the detected face region and using the geometric relations. To detect strong features of lighting variables by the changing surroundings, histogram matching, lip folding, and RASTA filter were applied, and the properties extracted by using the principal component analysis(PCA) were used for recognition. The result of the test has shown the processing speed between 1.15 and 2.35 sec. according to vocalizations in the embedded environment of CPU 806Mhz, RAM 128MB specifications and obtained 77% of recognition as 139 among 180 words were recognized.

Detection of HF Narrowband Signal with Unknown Frequency Using DFT Power Spectrum Averaging (DFT 전력스펙트럼 평균화를 기반으로 한 미지의 주파수를 가진 단파대 협대역 신호의 검출)

  • 김명진;김성필;오종갑
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.29-32
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    • 2000
  • 본 논문에서는 미지의 반송파주파수를 가진 협대역 신호의 존재를 광대역에서 검출하는 문제를 고려하였다. DFT 전력 스펙트럼을 평균화하여 주파수 영역에서 Neyman-Pearson criterion을 사용하여 신호를 검출하는 방법을 사용하였다. 평균화된 DFT 스펙트럼의 통계적 특성과 검출 threshold 및 검출 확률을 분석하여 보았다.

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딥러닝 기반 영상 조작 및 검출 기술 동향

  • O, Byeong-Tae
    • Broadcasting and Media Magazine
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    • v.27 no.2
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    • pp.62-69
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    • 2022
  • 다양한 목적으로 영상을 조작하려는 시도는 디지털 영상이 보편화되기 시작할 때부터 지속적으로 존재해 왔던 문제이며, 이러한 영상 조작의 유무를 검출하려는 시도 또한 지난 수십 년 동안 끊임없이 연구되어 왔다. 최근 빠르게 발전하는 인공지능 기술, 그 중에서도 딥러닝 기술을 이용하여 영상 조작을 검출하는 기술이 다양하게 발전되고 있지만, 한편으로는 딥러닝 기술을 이용하여 조작을 보다 정교하게 진행하거나 검출을 회피하려는 기술 또한 빠르게 발전하고 있다. 본 고에서는 영상을 조작하고, 검출하고 회피하는 기술 동향에 대하여 종합적으로 소개하고, 특히 딥러닝 기반의 기술이 각각의 영역에서 어떻게 적용되고 발전하고 있는지에 대하여 면밀히 살펴보고자 한다.

The Recusive Motion Detection Using Block Matching Between Moving Regions (움직임 영역간 블록 정합을 이용한 반복적인 움직임 검출)

  • 고봉수;김장형
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.580-583
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    • 2003
  • This paper presents the motion detection algorithm that can run robustly about recusive motion. The existing motion detection algorithm that uses difference image is robustly in some degree brightness or noise, but it frequently causes false alarms to temporal clutter, at the repetitive motion within a certain area. We developed a motion detection algorithm using mean absoulte error(MAE) which calculates the set of Moving regions and performs block matching. The experimental results revealed that our approach is superior to existing methodologies to handling various temporal clutter.

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Region Separateness-based Edge Detection Method (영역의 분할정도에 기반한 에지 검출 기법)

  • Seo, Suk-T.;Jeong, Hye-C.;Lee, In-K.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.939-944
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    • 2007
  • Edge is a significant element to represent boundary information between objects in images. There are various edge detection methods, which are based on differential operation, such as Sobel, Prewitt, Roberts, Canny, Laplacian, and etc. However the conventional methods have drawbacks as follow : (i) insensitivity to edges with gentle curve intensity, (ii) detection of double edges for edges with one pixel width. For the detection of edges, not only development of the effective operators but also that of appropriate thresholding methods are necessary. But it is very complicate problem to find an appropriate threshold. In this paper, we propose an edge detection method based on the region separateness between objects to overcome the drawbacks of the conventional methods, and a thresholding method for the proposed edge detection method. We show the effectiveness of the proposed method through experimental results obtained by applying the proposed and the conventional methods to well-known test images.

Robust Lane Detection Method in Varying Road Conditions (도로 환경 변화에 강인한 차선 검출 방법)

  • Kim, Byeoung-Su;Kim, Whoi-Yul
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.1
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    • pp.88-93
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    • 2012
  • Lane detection methods using camera, which are part of the driver assistance system, have been developed due to the growth of the vehicle technologies. However, lane detection methods are often failed by varying road conditions such as rainy weather and degraded lanes. This paper proposes a method for lane detection which is robust in varying road condition. Lane candidates are extracted by intensity comparison and lane detection filter. Hough transform is applied to compute the lane pair using lane candidates which is straight line in image. Then, a curved lane is calculated by using B-Snake algorithm. Also, weighting value is computed using previous lane detection result to detect the lanes even in varying road conditions such as degraded/missed lanes. Experimental results proved that the proposed method can detect the lane even in challenging road conditions because of weighting process.

Research of the Face Extract Algorithm from Road Side Images Obtained by vehicle (차량에서 획득된 도로 주변 영상에서의 얼굴 추출 방안 연구)

  • Rhee, Soo-Ahm;Kim, Tae-Jung;Kim, Moon-Gie;Yun, Duk-Geun;Sung, Jung-Gon
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.49-55
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    • 2008
  • The face extraction is very important to provide the images of the roads and road sides without the problem of privacy. For face extraction form roadside images, we detected the skin color area by using HSI and YCrCb color models. Efficient skin color detection was achieved by using these two models. We used a connectivity and intensity difference for grouping, skin color regions further we applied shape conditions (rate, area, number and oval condition) and determined face candidate regions. We applied thresholds to region, and determined the region as the face if black part was over 5% of the whole regions. As the result of the experiment 28 faces has been extracted among 38 faces had problem of privacy. The reasons which the face was not extracted were the effect of shadow of the face, and the background objects. Also objects with the color similar to the face were falsely extracted. For improvement, we need to adjust the threshold.

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Robust Face Detection Using Hybrid Filters and Convolutional Neural Networks (복합형 필터와 CNN 모델을 이용한 효과적인 얼굴 검출 기법)

  • Cho, Il-Gook;Park, Hyun-Jung;Kim, Ho-Joon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.05a
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    • pp.451-454
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    • 2005
  • 본 논문에서는 수정된 CNN(Convolutional Neural Network) 모델과 다중 필터가 상호 결합된 형태의 얼굴 패턴 검출 기법을 소개 한다. 이는 로봇 시각의 응용문제에서 실내영상의 실시간 인식문제를 대상으로 한다. 검출 과정의 효율성 향상을 위하여 도입된 다중 필터는 후보 영역의 개수와 범위를 줄일 수 있게 한다. 제안된 모델에서 CNN 신경망은 가보변환(Gabor Transform)계층을 두어 검출 과정의 첫 단계에서 영상 내의 기본 특징 지도를 생성 하도록 하였다. 보다 강인한 검출기능을 위하여 조명보정 기법이 시스템의 전처리 단계로 구현 된다. 실제 영상을 통한 실험 결과로부터 제안된 이론의 타당성을 고찰 한다.

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