• Title/Summary/Keyword: image of scientists

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Algorithm for Measuring Traffic Congestion using DCT (DCT를 이용한 교통 혼잡도 측정 알고리즘)

  • Cheong, Seong-Il;Ahn, Cheol-Woong;Choi, Byung-Geol;Kim, Sung-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.6 no.2
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    • pp.196-205
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    • 2000
  • As the number of cars is suddenly increasing, the number of cars on road exceeds the capacity of the road. In order to disperse the stream of traffic, there are many approaches for calculating the degree of congestion using traffic monitoring camera, and analyzing the velocity or the number of moving objects. Since those methods use background image, it is necessary to prepare the proper background image. In this paper, we proposed the algorithm to calculate the degree of congestion without background image. We perform DCT to the road image to obtain the edge information of cars, and then use it for calculating the degree of congestion.

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Clipart Image Retrieval System using Shape Information (모양 정보를 이용한 클립아트 이미지 검색 시스템)

  • Cheong, Seong-Il;Kim, Seung-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.1
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    • pp.116-125
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    • 2002
  • This paper presented a method of extracting shape information from a clipart image and then measured the similarity between clipart images using the extracted shape information. The results indicated that the outlines of the extracted clipart images were clearer that those of the original images. Previous methods of extracting shape information could be classified into outline-based methods and region-based methods. Included in the former category, the proposed method expressed the convex and concave aspects of an outline using the ratio of a rectangle. Accordingly, the proposed method was superior in expressing shape information than previous outline-based feature methods.

Robust Traffic Monitoring System by Spatio-Temporal Image Analysis (시공간 영상 분석에 의한 강건한 교통 모니터링 시스템)

  • 이대호;박영태
    • Journal of KIISE:Software and Applications
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    • v.31 no.11
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    • pp.1534-1542
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    • 2004
  • A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

Detection of Defects on Repeated Multi-Patterned Images (반복되는 다수 패턴 영상에서의 불량 검출)

  • Lee, Jang-Hee;Yoo, Suk-In
    • Journal of KIISE:Software and Applications
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    • v.37 no.5
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    • pp.386-393
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    • 2010
  • A defect in an image is a set of pixels forming an irregular shape. Since a defect, in most cases, is not easy to be modeled mathematically, the defect detection problem still resides in a research area. If a given image, however, composed by certain patterns, a defect can be detected by the fact that a non-defect area should be explained by another patch in terms of a rotation, translation, and noise. In this paper, therefore, the defect detection method for a repeated multi-patterned image is proposed. The proposed defect detection method is composed of three steps. First step is the interest point detection step, second step is the selection step of a appropriate patch size, and the last step is the decision step. The proposed method is illustrated using SEM images of semiconductor wafer samples.

Accelerating Depth Image-Based Rendering Using GPU (GPU를 이용한 깊이 영상기반 렌더링의 가속)

  • Lee, Man-Hee;Park, In-Kyu
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.11
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    • pp.853-858
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    • 2006
  • In this paper, we propose a practical method for hardware-accelerated rendering of the depth image-based representation(DIBR) of 3D graphic object using graphic processing unit(GPU). The proposed method overcomes the drawbacks of the conventional rendering, i.e. it is slow since it is hardly assisted by graphics hardware and surface lighting is static. Utilizing the new features of modem GPU and programmable shader support, we develop an efficient hardware-accelerating rendering algorithm of depth image-based 3D object. Surface rendering in response of varying illumination is performed inside the vertex shader while adaptive point splatting is performed inside the fragment shader. Experimental results show that the rendering speed increases considerably compared with the software-based rendering and the conventional OpenGL-based rendering method.

Multiple Region-of-Interest Based Image Retrieval Method (다중 관심영역 기반 이미지 검색 방법)

  • Lee, Jong-Won;Nang, Jong-Ho
    • Journal of KIISE:Computer Systems and Theory
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    • v.37 no.5
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    • pp.314-318
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    • 2010
  • This paper proposes an image retrieval method based on the Multiple Region-of-Interest. In the proposed method, the image is segmented into blocks, among which the blocks overlapped with multiple ROIs are selected. The similarity of images is measured using the MPEG-7 dominant color descriptor(DCD) and considering the relative location of the overlapped blocks. The experimental results showed that the proposed method improves the retrieval performance than the previous methods using the global DCD or comparing the blocks at the same position. In addition, the method that considers the relative position of blocks overlapped with the multiple ROIs also showed a better performance than the existing methods.

Linear Feature Extraction from Satellite Imagery using Discontinuity-Based Segmentation Algorithm

  • Niaraki, Abolghasem Sadeghi;Kim, Kye-Hyun;Shojaei, Asghar
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.643-646
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    • 2006
  • This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

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Alphabetical Gesture Recognition using HMM (HMM을 이용한 알파벳 제스처 인식)

  • Yoon, Ho-Sub;Soh, Jung;Min, Byung-Woo
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.384-386
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    • 1998
  • The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interaction(HCI). Many methods hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMMs is proposed for alphabetical hand gesture recognition. In the preprocessing stage, the proposed approach consists of three different procedures for hand localization, hand tracking and gesture spotting. The hand location procedure detects the candidated regions on the basis of skin-color and motion in an image by using a color histogram matching and time-varying edge difference techniques. The hand tracking algorithm finds the centroid of a moving hand region, connect those centroids, and thus, produces a trajectory. The spotting a feature database, the proposed approach use the mesh feature code for codebook of HMM. In our experiments, 1300 alphabetical and 1300 untrained gestures are used for training and testing, respectively. Those experimental results demonstrate that the proposed approach yields a higher and satisfying recognition rate for the images with different sizes, shapes and skew angles.

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A Method of Gray Level Shape-Based Interpolation in Medical Image (의학 영상에서의 그레이 수준 형태 기반 보간 기법)

  • Sung, Won;Kim, Eui-Jung;Park, Jong-Won
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.520-522
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    • 2002
  • 오늘날 CT나 MR등을 통한 의학 영상 기술과 컴퓨터 성능의 향상으로 인체 내부 장기의 영상을 비교적 용이하게 얻을 수 있으며 얻어진 영상 정보는 컴퓨터로 수치화 되므로 데이터의 조작 및 가공이 용이하다. 그러나, 이렇게 얻어진 의학 영상들은 보통 2차원적 슬라이스 image 형태로 얻어진다. 일반적으로 슬라이스 사이의 간격은 조사량 등 여러 문제 때문에, 항상 동일한 간격을 유지하고 있지 않은 경우가 많으며 슬라이스 사이 간격이 슬라이스 내의 픽셀 간격보다 큰 경우가 대부분이다. 이러한 image로부터 3차원적 디스플레이나, 조작, 분석을 하기 위해서는 같은 간격의 image를 얻어야 한다. 이러한 이유로 인하여 보간(Interpolation) 기법이 의학 영상 분야에서 많이 사용된다. 본 논문은 명태-기반 보간 방법을 gray-scale image에 적용이 가능하도록 확장한 그레이 수준 형태 기반 보간 알고리즘을 구현하였다. 그리하여, 본 논문이 제안한 알고리즘을 슬라이스 간격이 큰 2차원 복부 CT 영상에 적용시켜 다른 보간법들보다 향상된 결과를 확인할 수 있었다.

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A Data Type for Concept-Based Retrieval against Image Databases Indefinitely Indexed (불확정적으로 색인된 이미지 데이터베이스를 개념 기반으로 검색하기 위한 자료형)

  • Yang, Jae-Dong
    • Journal of KIISE:Databases
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    • v.29 no.1
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    • pp.27-33
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    • 2002
  • There are two significant drawbacks in triple image indexing; one is that is cannot support concept-based image retrieval and the other is that it fails to allow disjunctive labeling of images. To remedy the drawbacks, we propose a new technique supporting a concept-based retrieval against images indexed by indefinite fuzzy triples (I-fuzzy triples). The I-fuzzy triples allow not only a disjunctive image labeling, but also a concept-based matching against images labeled disjunctively. The disjunctive labeling is based on the expended closed world assumption and the concept-based image retrieval is based on fuzzy matching. In this paper, we also propose a concept-based query evaluation against the image database to extract desired answers with the degree of certainty $\alpha$$\in$[1,0].