• Title/Summary/Keyword: computer image analysis

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경계의 값 분포 특성과 정보를 기반한 새로운 경계 영상 압축 기법 (New Still Edge Image Compression based on Distribution Characteristics of the Value and the Information on Edge Image)

  • 김도현;한종우;김윤
    • 한국멀티미디어학회논문지
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    • 제19권6호
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    • pp.990-1002
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    • 2016
  • In this paper, we propose a new compression method for the edge image by analyzing the characteristics and the distribution of pixel values of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are `0`. By these analyses we suggest the Zero-Based codec that expresses all values in a CU by a single bit flag. Also, in order to reduce the computational complexity of the proposed codec, the block partition and the intra-prediction techniques are proposed by using edge information like the number of each edge direction, the distribution and the amplitude of a major edge direction in the CU. Experimental results show that the proposed codec leads to a slighter distortion in Y domain than that of HEVC, but has far faster processing speed up to 53 times while it maintains the similar image quality compared to HEVC.

가상공간 융합을 위한 다중 카메라 영상 특징 분석 (Multi-camera image feature analysis for virtual space convergence)

  • 윤종호;최명렬;이상선
    • 한국융합학회논문지
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    • 제8권5호
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    • pp.19-28
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    • 2017
  • 본 논문은 가상공간 제작을 위해 다수의 카메라로 영상을 촬영했을 때, 영상 특성 차이를 감소시키는 방법을 제안하였다. 각각 8 개의 본체와 렌즈를 교차 장착하여 64 개의 영상을 사용하였다. 영상 분석은 히스토그램과 픽셀 분포 값의 표준 편차를 분석 비교하였다. 분석결과, 동일 기종의 카메라임에도 불구하고, 렌즈 혹은 이미지 센서에 따라 각각 다른 영상 특성을 보여주었다. 본 논문에서는 이러한 차이를 보정하기 위해 영상의 전체 밝기 값의 분포를 조절하였다. 시뮬레이션 결과, 평균 편차가 최대 (실내 : 6.89, 실외 : 24.23) 이었으나, 시뮬레이션 진행 후 편차가 거의(실내 : 최대 0.42, 실외 : 최대 : 2.73) 없는 영상을 얻었다. 추후에는 영상 밝기 분포보다 정밀한 영상 분석 방법을 연구하고 적용할 것이다.

전두골 결손 마우스 모델의 골형성 자동 분석 (Automatic Analysis of Bone Formation in a Mouse Model of Frontal Bone Defect)

  • 강선경;정성태
    • 한국멀티미디어학회논문지
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    • 제18권9호
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    • pp.997-1007
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    • 2015
  • In this paper, we propose a method for automatically analyzing the bone formation in a mouse model of frontal bone defect. We perforate two holes of 0.8mm diameter in the frontal bone and observe the bone formation process using a micro CT. Because the conventional analysis software of the micro CT does not support automatic analysis of the bone formation status, we have to use a manual analysis method. However the manual analysis is very cumbersome and requires a lot of time, we propose an automatic analysis method. It rotates the image around three axes directions so that the mouse's skull come into regular position. It calculates the cumulative image of the voxel values for the perforated bone surface. It estimates the hole location by finding the darkest point in the cumulative image. The proposed method was applied to 24 CT images of saline administration group and PTH administration group and hole location was estimated. BV/TV index was calculated for the estimated hole to evaluate the bone formation status. Experimental results showed that bone formation process is more active in PTH administration group. The method proposed in this paper could replace successfully the cumbersome and time consuming manual job.

용광로 연소대 관리시스템 개발 (Development of combustion zone monitoring system for a blast furnace)

  • 최태화
    • 제어로봇시스템학회논문지
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    • 제3권3호
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    • pp.318-322
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    • 1997
  • A prototype of combustion zone monitoring system as been developed and installed into tuyeres of the blast furnace. The system consists of CCD(charge coupled device) cameras, sonic flow meters, an image processor and a personal computer. The personal computer collects raceway luminance data and operational data from the image processor that is connected to the color CCD camera from the blast furnace process computer, respectively. In addition, the sonic flow meters supply coal injection rate data to the personal computer. Then, the personal computer evaluates the combustion conditions with the raceway inspection algorithm. This integrated monitoring system allows us to detect abnormal raceway conditions and the clogging status of coal injection pipe. The image processing techniques of the system enable us to effectively monitor unburnt coal sticking to tuyere tip and injection lance wear conditions. Such a developed system ensures rapid and precise raceway inspection. The image processing capability of the system has helped operator to early detect both the unburnt coal sticking problem and the errosion problem of injection lance. Furthermore, the system could control the abnormal raceway condition based the the analysis results obtained from combustion monitoring.

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A Efficient Image Separation Scheme Using ICA with New Fast EM algorithm

  • Oh, Bum-Jin;Kim, Sung-Soo;Kang, Jee-Hye
    • 한국지능시스템학회논문지
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    • 제14권5호
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    • pp.623-629
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    • 2004
  • In this paper, a Efficient method for the mixed image separation is presented using independent component analysis and the new fast expectation-maximization(EM) algorithm. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme in various applications. However, it has been known that ICA does not establish good performance in source separation by itself. So, Innovation process which is one of the methods that were employed in image separation using ICA, which produces improved the mixed image separation. Unfortunately, the innovation process needs long processing time compared with ICA or EM. Thus, in order to overcome this limitation, we proposed new method which combined ICA with the New fast EM algorithm instead of using the innovation process. Proposed method improves the performance and reduces the total processing time for the Image separation. We compared our proposed method with ICA combined with innovation process. The experimental results show the effectiveness of the proposed method by applying it to image separation problems.

EAR: Enhanced Augmented Reality System for Sports Entertainment Applications

  • Mahmood, Zahid;Ali, Tauseef;Muhammad, Nazeer;Bibi, Nargis;Shahzad, Imran;Azmat, Shoaib
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권12호
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    • pp.6069-6091
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    • 2017
  • Augmented Reality (AR) overlays virtual information on real world data, such as displaying useful information on videos/images of a scene. This paper presents an Enhanced AR (EAR) system that displays useful statistical players' information on captured images of a sports game. We focus on the situation where the input image is degraded by strong sunlight. Proposed EAR system consists of an image enhancement technique to improve the accuracy of subsequent player and face detection. The image enhancement is followed by player and face detection, face recognition, and players' statistics display. First, an algorithm based on multi-scale retinex is proposed for image enhancement. Then, to detect players' and faces', we use adaptive boosting and Haar features for feature extraction and classification. The player face recognition algorithm uses boosted linear discriminant analysis to select features and nearest neighbor classifier for classification. The system can be adjusted to work in different types of sports where the input is an image and the desired output is display of information nearby the recognized players. Simulations are carried out on 2096 different images that contain players in diverse conditions. Proposed EAR system demonstrates the great potential of computer vision based approaches to develop AR applications.

Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches

  • Yu, Ning;Yu, Zeng;Gu, Feng;Li, Tianrui;Tian, Xinmin;Pan, Yi
    • Journal of Information Processing Systems
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    • 제13권2호
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    • pp.204-214
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    • 2017
  • Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

정지영상 데이터베이스의 효율적 인식자 생성 (Efficient Generation of Image Identifiers for Image Database)

  • 박제호
    • 반도체디스플레이기술학회지
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    • 제10권3호
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    • pp.89-94
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    • 2011
  • The image identification methodology associates an image with a unique identifiable representation. Whenever the methodology regenerates an identifier for the same image, moreover, the newly created identifier needs to be consistent in terms of representation value. In this paper, we discuss a methodology for image identifier generation utilizing luminance correlation. We furthermore propose a method for performance enhancement of the image identifier generation. We also demonstrate the experimental evaluations for uniqueness and similarity analysis and performance improvement that have shown favorable results.

멀티미디어 PCS에서 Image/Voice/Data 호에 대한 가변적 보호채널 할당의 분석 (Analysis of Variable Guard Channel Allocation For Image/Voice/Data Calls in Multimedia Personal Communication Services)

  • 나원식;이용주
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2000년도 제13회 춘계학술대회 및 임시총회 학술발표 논문집
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    • pp.692-697
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    • 2000
  • 멀티미디어 개인 휴대 통신(MPCS)에서 다중 클래스호에 대한 효율적인 채널할당은 매우 중요하다고 할 수 있다. 본 논문에서는 Image/Voice/Data 호에 대하여 가변적 보호 채널을 할당하는 새로운 방식을 제안하였다. 이러한 방식은 3차원 상태 천이도로 모델링 되며 보호 채널의 크기를 가변적으로 조절함으로써 보다 융통성있는 서비스를 제공하게 되며, 또한 수학적 분석과 시뮬레이션을 통해 비교분석을 수행하였다.

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위성 영상의 효과적인 분석을 위한 밝기와 크로스 엔트로피 기반의 그림자 검출 (Shadow Detection Based Intensity and Cross Entropy for Effective Analysis of Satellite Image)

  • 박기홍
    • 한국항행학회논문지
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    • 제20권4호
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    • pp.380-385
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    • 2016
  • 그림자는 자연 영상에서 관찰되는 물리적인 현상이지만 위성 영상 분석에 부정적인 영향을 미치는 요소로 컴퓨터 비전의 전처리 과정에서 그림자 검출 과정은 매우 중요하다. 본 논문에서는 싱글 영상 기반의 위성 영상에서 효과적인 영상 분석을 위해 그림자를 검출하는 방법으로 크로스 엔트로피와 밝기 영상을 이용해 그림자를 검출하는 방법을 제안하였다. 칼라 영상을 그레이 레벨 영상으로 변환한 후 크로스 엔트로피를 기반으로 최적의 임계값을 추정하여 첫 번째 그림자 후보 영역으로 판별하였고, 칼라 영상의 밝기 영상을 이용해 최종 그림자 영역을 검출하였다. 제안하는 방법의 타당성을 위해 위성 영상들을 대상으로 실험하였고, 실험 결과 제안하는 그림자를 검출 방법이 효과적으로 수행됨을 확인하였다.