• Title/Summary/Keyword: Vector map

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Fractal Depth Map Sequence Coding Algorithm with Motion-vector-field-based Motion Estimation

  • Zhu, Shiping;Zhao, Dongyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.1
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    • pp.242-259
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    • 2015
  • Three-dimensional video coding is one of the main challenges restricting the widespread applications of 3D video and free viewpoint video. In this paper, a novel fractal coding algorithm with motion-vector-field-based motion estimation for depth map sequence is proposed. We firstly add pre-search restriction to rule the improper domain blocks out of the matching search process so that the number of blocks involved in the search process can be restricted to a smaller size. Some improvements for motion estimation including initial search point prediction, threshold transition condition and early termination condition are made based on the feature of fractal coding. The motion-vector-field-based adaptive hexagon search algorithm on the basis of center-biased distribution characteristics of depth motion vector is proposed to accelerate the search. Experimental results show that the proposed algorithm can reach optimum levels of quality and save the coding time. The PSNR of synthesized view is increased by 0.56 dB with 36.97% bit rate decrease on average compared with H.264 Full Search. And the depth encoding time is saved by up to 66.47%. Moreover, the proposed fractal depth map sequence codec outperforms the recent alternative codecs by improving the H.264/AVC, especially in much bitrate saving and encoding time reduction.

Performance Improvement of Map Matching Using Compensation Vectors (보정벡터를 이용한 맵 매칭의 성능 향상)

  • Ahn Do-Rang;Lee Dong-Wook
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.2
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    • pp.97-103
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    • 2005
  • Most car navigation systems(CNS) estimate the vehicle's location using global positioning system(GPS) or dead reckoning(DR) system. However, the estimated location has undesirable errors because of various noise sources such as unpredictable GPS noises. As a result, the measured position is not lying on the road, although the vehicle is known to be restricted on the road network. The purpose of map matching is to locate the vehicle's position on the road network where the vehicle is most likely to be positioned. In this paper, we analyze some general map matching algorithms first. Then, we propose a map matching method using compensation vectors to improve the performance of map matching. The proposed method calculates a compensation vector from the discrepancy between a measured position and an estimated position. The compensation vector and a newly measured position are to be used to determine the next estimation. To show the performance improvement of the map matching using compensation vectors, the real time map matching experiments are performed. The real road experiments demonstrate the effectiveness and applicability of the proposed map matching.

Low Sit Rate Image Coding using Neural Network (신경망을 이용한 저비트율 영상코딩)

  • 정연길;최승규;배철수
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.579-582
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    • 2001
  • Vector Transformation is a new method unified vector quantization and coding. So far, codebook generation applied to coding was LBG algorithm. But using the advantage of SOFM(Self-Organizing Feature Map) based on neural network can improve a system's performance. In this paper, we generated VTC(Vector Transformation Coding) codebook applied with SOFM algorithm and compare the result for several coding rates with LBG algorithm. The problem of Vector quantization is complicated calculation and codebook generation. So, to solve this problem, we used neural network approach method.

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A METHOD OF IMAGE DATA RETRIEVAL BASED ON SELF-ORGANIZING MAPS

  • Lee, Mal-Rey;Oh, Jong-Chul
    • Journal of applied mathematics & informatics
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    • v.9 no.2
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    • pp.793-806
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    • 2002
  • Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

Digital Map Watermarking Using sakamoto algorithm (사카모토의 방법을 이용한 수치지도 워터마킹)

  • Park, Kyi-Tae;Kim, Kab-Il;Kang, Hwan-Il;Han, Seung-Soo
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2797-2799
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    • 2002
  • In this paper, the algorithm is suggested for inserting and extracting the watermark in the digital map of vector form. This kind of algorithm was first anounced by the sakamoto[1]. In order to use watermarking in the digital map, the map is analyzed and experimented to protect the map data. As for the vector watermarking, there are few references and need more research for the theoretical back ground. As for this, in this paper, experiment of the immunity against the noise is conducted for the selection of the proper immunity factor.

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Abnormal Vibration Diagnostics Algorithm of Rotating Machinery Using Self-Organizing Feature Map nad Learing Vector Quantization (자기조직화특징지도와 학습벡터양자화를 이용한 회전기계의 이상진동진단 알고리듬)

  • 양보석;서상윤;임동수;이수종
    • Journal of KSNVE
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    • v.10 no.2
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    • pp.331-337
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    • 2000
  • The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal defect diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised learning algorithm is used to improve the quality of the classifier decision regions.

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A Design and Implementation of GIS Vector Map Converting Engine (GIS Vector Map 변환 엔진의 설계 및 구현)

  • Choi Jae-Young;Kim Myung-Sam;Chung Yeong-Jee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.11a
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    • pp.789-792
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    • 2004
  • 위치기반 서비스의 기초적인 부분이며 필수적인 부분이 바로 사용자가 자신의 위치에 대한 인지를 명확하게 할 수 있도록 위치를 표시하고 보여주기 위한 지도 데이터 서비스이다. 지도 데이터 서비스를 위해서는 지리정보를 특정 어플리케이션에 의존함이 없이 즉시 볼 수 있는 형태의 포맷으로 변환하는 것이 필요하다. 이를 충족시킬 수 있는 포맷으로 웹브라우저 상에서 바로 볼 수 있는 SVG를 고려할 수 있다. 본 논문에서는 GIS Vector Map의 대표적인 파일 형식인 DXF, SHP, MIF를 분석하였다. 또한, 이들 파일 형식을 공통된 하나의 파일형식인 XML로 변환하여 DB를 구축하고, 구축된 XML 데이터를 SVG로 변환하는 엔진을 구현하였으며 이를 통하여 $98\%$이상의 변환 효율을 갖는 결과를 얻을 수 있었다.

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A Visualization Method for the Ocean Forecast Data using WMS System (WMS 시스템을 이용한 해양예측모델 데이터의 가시화 기법)

  • Kwon, Taejung;Lee, Jaeryoung;Park, Jaepyo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.6
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    • pp.11-19
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    • 2018
  • Recently, many companies offer various web-based map that is based on GIS(Geographic Information System) information. Google Map, Open street, Bing Map, Naver Map, Daum Map, Vwolrd Map, etc are the few examples of such system. In this paper, we propose a method to visualize ocean forecasting model data considering the flow diagram of tidal current, streamline expression algorithm, and user convenience by using vector field data information that is currently being served. It is confirmed that the proposed method of the flow diagram of tidal current, and stream line expression algorithm is faster than that of conventional ocean prediction model data by more than 2 times.

Motion Field Estimation Using U-disparity Map and Forward-Backward Error Removal in Vehicle Environment (U-시차 지도와 정/역방향 에러 제거를 통한 자동차 환경에서의 모션 필드 예측)

  • Seo, Seungwoo;Lee, Gyucheol;Lee, Sangyong;Yoo, Jisang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.12
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    • pp.2343-2352
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    • 2015
  • In this paper, we propose novel motion field estimation method using U-disparity map and forward-backward error removal in vehicles environment. Generally, in an image obtained from a camera attached in a vehicle, a motion vector occurs according to the movement of the vehicle. but this motion vector is less accurate by effect of surrounding environment. In particular, it is difficult to extract an accurate motion vector because of adjacent pixels which are similar each other on the road surface. Therefore, proposed method removes road surface by using U-disparity map and performs optical flow about remaining portion. forward-backward error removal method is used to improve the accuracy of the motion vector. Finally, we predict motion of the vehicle by applying RANSAC(RANdom SAmple Consensus) from acquired motion vector and then generate motion field. Through experimental results, we show that the proposed algorithm performs better than old schemes.

Application and Evaluation of Vector Map Watermarking Algorithm for Robustness Enhancement (강인성 향상을 위한 벡터 맵 워터마킹 알고리즘의 적용과 평가)

  • Won, Sung Min;Park, Soo Hong
    • Spatial Information Research
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    • v.21 no.3
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    • pp.31-43
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    • 2013
  • Although the vector map data possesses much higher values than other types of multimedia, the data copyright and the protection against illegal duplication are still far away from the attention. This paper proposes a novel watermarking technique which is both robust to diverse attacks and optimized to a vector map structure. Six approaches are proposed for the design of the watermarking algorithm: point-based approach, building a minimum perimeter triangle, watermark embedding in the length ratio, referencing to the pixel position of the watermark image, grouping, and using the one-way function. Our method preserves the characteristics of watermarking such as embedding effectiveness, fidelity, and false positive rate, while maintaining robustness to all types of attack except a noise attack. Furthermore, our method is a blind scheme in which robustness is independent of the map data. Finally, our method provides a solution to the challenging issue of degraded robustness under severe simplification attacks.