• Title/Summary/Keyword: Map Size

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Adaptive Image Content-Based Retrieval Techniques for Multiple Queries (다중 질의를 위한 적응적 영상 내용 기반 검색 기법)

  • Hong Jong-Sun;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.73-80
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    • 2005
  • Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

Multi-view Image Generation from Stereoscopic Image Features and the Occlusion Region Extraction (가려짐 영역 검출 및 스테레오 영상 내의 특징들을 이용한 다시점 영상 생성)

  • Lee, Wang-Ro;Ko, Min-Soo;Um, Gi-Mun;Cheong, Won-Sik;Hur, Nam-Ho;Yoo, Ji-Sang
    • Journal of Broadcast Engineering
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    • v.17 no.5
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    • pp.838-850
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    • 2012
  • In this paper, we propose a novel algorithm that generates multi-view images by using various image features obtained from the given stereoscopic images. In the proposed algorithm, we first create an intensity gradient saliency map from the given stereo images. And then we calculate a block-based optical flow that represents the relative movement(disparity) of each block with certain size between left and right images. And we also obtain the disparities of feature points that are extracted by SIFT(scale-invariant We then create a disparity saliency map by combining these extracted disparity features. Disparity saliency map is refined through the occlusion detection and removal of false disparities. Thirdly, we extract straight line segments in order to minimize the distortion of straight lines during the image warping. Finally, we generate multi-view images by grid mesh-based image warping algorithm. Extracted image features are used as constraints during grid mesh-based image warping. The experimental results show that the proposed algorithm performs better than the conventional DIBR algorithm in terms of visual quality.

A Knowledge Map Based on a Keyword-Relation Network by Using a Research Paper Database in the Computer Engineering Field (컴퓨터공학 분야 학술 논문 데이터베이스를 이용한 키워드 연관 네트워크 기반 지식지도)

  • Jung, Bo-Seok;Kwon, Yung-Keun;Kwak, Seung-Jin
    • The KIPS Transactions:PartD
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    • v.18D no.6
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    • pp.501-508
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    • 2011
  • A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

Design of In-Wheel Motor for Automobiles Using Parameter Map (파라미터 맵을 이용한 차량용 인휠 전동기의 설계)

  • Kim, Hae-Joong;Lee, Choong-Sung;Hong, Jung-Pyo
    • Journal of the Korean Magnetics Society
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    • v.25 no.3
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    • pp.92-100
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    • 2015
  • Electric Vehicle (EV) can be categorized by the driving method into in-wheel and in-line types. In-wheel type EV does not have transmission shaft, differential gear and other parts that are used in conventional cars, which simplifies and lightens the structure resulting in higher efficiency. In this paper, design method for in-wheel motor for automobiles using Parameter Map is proposed, and motor with continuous power of 5 kW is designed, built and its performance is verified. To decide the capacity of the in-wheel motor that meets the automobile's requirement, Vehicle Dynamic Simulation considering the total mass of vehicle, gear efficiency, effective radius of tire, slope ratio and others is performed. Through this step, the motor's capacity is decided and initial design to determine the motor shape and size is performed. Next, the motor parameters that meet the requirement is determined using parametric design that uses parametric map. After the motor parameters are decided using parametric map, optimal design to improve THD of back EMF, cogging torque, torque ripple and other factors is performed. The final design was built, and performance analysis and verification of the proposed method is conducted by performing load test.

Production and Accuracy Analysis of Topographic Status Map Using Drone Images (드론영상을 이용한 지형 현황도 제작 및 정확도 분석)

  • Kim, Doopyo;Back, Kisuk;Kim, Sungbo
    • Journal of the Korean GEO-environmental Society
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    • v.22 no.2
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    • pp.35-39
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    • 2021
  • Photogrammetry using drone can produce high-resolution ortho image and acquire high-accuracy 3D information, which is useful. Therefore, this study attempted to determine the possibility of using drone-photogrammetry in park construction by producing a topographic map using drone-photogrammetry and analyzing the problems and accuracy generated during production. For this purpose, we created ortho image and DSM (digital surface model) using drone images and created topographic status map by vectorizing them. Accuracy was compared based on topographic status map by GPS (global positioning system) and TS (total station). The resulting of analyzing mean of the residuals at check points showed that 0.044 m in plane and 0.066 m in elevation, satisfying the tolerance range of 1/1,000 numerical maps, and result of compared lake size showed a difference of about 4.4%. On the other hand, it was difficult to obtain accurate height values for terrain in which existed vegetation when producing the topographic map, and in the case of underground buried objects, it is not possible to confirm it in the image, so direct spatial information acquisition was necessary. Therefore, it is judged that the topographic status map using drone photogrammetry can be efficiently constructed if direct spatial data acquisition is achieved for some terrain.

128-Bit Chaotic Block Encryption Scheme Using a PLCM (PLCM을 이용한 128비트 카오스 블록 암호화 기법)

  • Lee, Sung-Woo;Lee, Min-Goo;Park, Jeong-Yeol;Shin, Jae-Ho
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • v.4 no.2
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    • pp.19-27
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    • 2005
  • In this paper, we propose 128-bit chaotic block encryption scheme using a PLCM (Piecewise Linear Chaotic Map) having a good dynamical property. The proposed scheme has a block size of 128- bit and a key size of 128-bit. The encrypted code is generated from the output of PLCM. We show the proposed scheme is very secure against statistical attacks and have very good avalanche effect and randomness properties.

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VARIOGRAM-BASED URBAN CHARACTERIZATION USING HIGH RESOLUTION SATELLITE IMAGERY

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.413-416
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    • 2006
  • As even small features can be classified as high resolution imagery, urban remote sensing is regarded as one of the important application fields in time of wide use of the commercialized high resolution satellite imageries. In this study, we have analyzed the variogram properties of high resolution imagery, which was obtained in urban area through the simple modeling and applied to the real image. Based on the grasped variogram characteristics, we have tried to decomposed two high-resolution imagery such as IKONOS and QuickBird reducing window size until the unique variogram that urban feature has come out and then been indexed. Modeling results will be used as the fundamental data for variographic analysis in urban area using high resolution imagery later on. Index map also can be used for determining urban complexity or land-use classification, because the index is influenced by the feature size.

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Face Recognition using the Feature Space and the Image Vector (세그멘테이션에 의한 특징공간과 영상벡터를 이용한 얼굴인식)

  • 김선종
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.7
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    • pp.821-826
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    • 1999
  • This paper proposes a face recognition method using feature spaces and image vectors in the image plane. We obtain the 2-D feature space using the self-organizing map which has two inputs from the axis of the given image. The image vector consists of its weights and the average gray levels in the feature space. Also, we can reconstruct an normalized face by using the image vector having no connection with the size of the given face image. In the proposed method, each face is recognized with the best match of the feature spaces and the maximum match of the normally retrieval face images, respectively. For enhancing recognition rates, our method combines the two recognition methods by the feature spaces and the retrieval images. Simulations are conducted on the ORL(Olivetti Research laboratory) images of 40 persons, in which each person has 10 facial images, and the result shows 100% recognition and 14.5% rejection rates for the 20$\times$20 feature sizes and the 24$\times$28 retrieval image size.

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Performance Improvement of Turbo Code in low SNR and short frame sizes (낮은 SNR과 짧은 프레임에서 터보코드 성능 개선)

  • 정상연;이용식;심우성;허도근
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.61-64
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    • 1999
  • The turbo code appropriate to IMT-2000 is known to have a good performance whenever the size of frame increases. But it is not appropriate to a sort of video service to need real time because of decoding complexity and long delay time by the size of frame. Therefore this paper proposes decoding decision algorithm of short frame in which soft output is weighted according to iteration number in turbo decoder. Performance of the proposed algorithm is analysed in the AWGN channel when short length of frame is 100, 256, 640. As the result. it is appeared that the proposed decoding decision algorithm has improved in BER other than in the existing MAP decoding algorithm.

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Development of Obstacle Database Management Module for Obstacle Estimation and Clustering: G-eye Management System (장애물 추정 및 클러스터링을 위한 장애물 데이터베이스 관리 모듈 개발: G-eye 관리 시스템)

  • Min, Seonghee;Oh, Yoosoo
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.344-351
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    • 2017
  • In this paper, we propose the obstacle database management module for obstacle estimation and clustering. The proposed G-eye manager system can create customized walking route for blind people using the UI manager and verify the coordinates of the path. Especially, G-eye management system designed a regional information module. The regional information module can improve the loading speed of the obstacle data by classifying the local information by clustering the coordinates of the obstacle. In this paper, we evaluate the reliability of the walking route generated from the obstacle map. We obtain the coordinate value of the path avoiding the virtual obstacle from the proposed system and analyze the error rate of the path avoiding the obstacle according to the size of the obstacle. And we analyze the correlation between obstacle size and route by classifying virtual obstacles into sizes.