• Title/Summary/Keyword: 벡터맵 데이터

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Effective Compression Technique for Secure Transmission and Storage of GIS Digital Map (GIS 디지털 맵의 안전한 전송 및 저장을 위한 효율적인 압축 기법)

  • Jang, Bong-Joo;Moon, Kwang-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.14 no.2
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    • pp.210-218
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    • 2011
  • Generally, GIS digital map has been represented and transmitted by ASCII and Binary data forms. Among these forms, Binary form has been widely used in many GIS application fields for the transmission of mass map data. In this paper, we present a hierarchical compression technique of polyline and polygon components for effective storage and transmission of vector map with various degree of decision. These components are core geometric components that represent main layers in vector map. The proposed technique performs firstly the energy compaction of all polyline and polygon components in spatial domain for the lossless compression of detailed vector map and compress independently integer parts and fraction parts of 64bit floating points. From experimental results, we confirmed that the proposed technique has superior compressive performance to the conventional data compression of 7z, zip, rar and gz.

Contents Based Partial Encryption of GIS Vector Map (GIS 벡터맵의 콘텐츠 기반 선택적 암호화 기술)

  • Jang, Bong-Joo;Lee, Suk-Hwan;Moon, Kwang-Seok;Kwon, Ki-Ryong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.5
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    • pp.88-98
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    • 2011
  • Recently, according as the importance of GIS(geography information system) database security is embossed, much researches had been achieved about GIS network security. But most such researches are weak against sourceful illegal reproductions and distributions of GIS vector data map. In this paper, we proposed an efficient layer unit contents based partial encryption technique in the vector map compression domain to prevent illegal distributions and unauthorized accesses. This method achieves a partial encryption about each central coordinate and directional parameters of a MCA(minimum coding attribute) that is created at the vector map compression processing in the vector space. First, the position encryption is applied as permutating randomly the center coordinate of each record that is minimum unit of vector map shape. And second, the direction encryption that changing shapes of vector map topography is applied as encrypting the direction of vertices's coordinates of each record. In experimental results, we confirmed that our proposed method can encipher the large volumed vector map data effectively in low computational complexity. Also, we could minimize the decline of compression efficiency that occurred by conventional contents based encryption schemes using AES or DES algorithms.

Hybrid Polyline Simplification for GIS Vector Map Data Compression (GIS 벡터맵 데이터 압축을 위한 혼합형 폴리라인 단순화)

  • Im, Dae-Yeop;Jang, Bong-Joo;Lee, Suk-Hwan;Kwon, Seong-Geun;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.16 no.4
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    • pp.418-429
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    • 2013
  • This paper presents a GIS vector map data compression scheme based on hybrid polyline simplification method and SEC(spatial energy compaction). The proposed method extracts all layers which contain polylines in the GIS vector map and compress all polylines in extracted layers by the hybrid polyline simplification and SEC based on MAE(minimum area error) for each segment in the line. The proposed simplification and SEC increase the compression ratio while preserving the shape quality. We analyze the visual aspects and compression efficiency between the original GIS vector map and the compressed map. From experimental results, we verify that our method has the higher compression efficiency and visual quality than conventional methods.

A Study of NormalMap Texture in Game Engine (게임엔진에서의 노말맵 텍스쳐에 대한 연구)

  • Jung, Jong-Pil
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.01a
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    • pp.203-205
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    • 2020
  • 본 논문에서는 게임 엔진에서 사용되는 노말맵(Normal Map)의 원리와 그 응용 방식에 대해 연구하였다. 노말맵은 게임에서 하이 폴리곤 모델링에 적용되는 조명 적용 데이터를 로우 폴리곤에 적용할 수 있는 기술로, 하이 폴리곤 모델링의 벡터 방향 데이터를 텍스쳐로 저장하여 로우 폴리곤에 적용해서 벡터 방향을 텍셀단위로 조정할 수 있게 한다. 여기에서는 게임에서의 노말맵 저장 방식과 연산 방식에 대해 소개하고 이를 응용하여 최적화 시킬 수 있는 방법에 대해 연구한다.

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New Image Editor based on Combination of Bitmap and Vector Method (비트맵과 벡터방식을 혼합한 새로운 이미지 편집기)

  • 김진호;이규남;나인호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.2
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    • pp.288-293
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    • 2002
  • It is possible to classify image data into two types according to the internal representation: one is bitmap, the other is vector. A bitmap image is represented by the two dimensional pixels whereas a vector image is represented by mathematical functions to draw vector objects such as line, rectangle and circle on the two or three dimensional space. So it is necessary for users to use a individual application program for each different image. In this paper, we present a method for design and implementation of image editing tool based on combining of bitmap and vector image.

GIS Vector Map Compression using Spatial Energy Compaction based on Bin Classification (빈 분류기반 공간에너지집중기법을 이용한 GIS 벡터맵 압축)

  • Jang, Bong-Joo;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.3
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    • pp.15-26
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    • 2012
  • Recently, due to applicability increase of vector data based digital map for geographic information and evolution of geographic measurement techniques, large volumed GIS(geographic information service) services having high resolution and large volumed data are flowing actively. This paper proposed an efficient vector map compression technique using the SEC(spatial energy compaction) based on classified bins for the vector map having 1cm detail and hugh range. We encoded polygon and polyline that are the main objects to express geographic information in the vector map. First, we classified 3 types of bins and allocated the number of bits for each bin using adjacencies among the objects. and then about each classified bin, energy compaction and or pre-defined VLC(variable length coding) were performed according to characteristics of classified bins. Finally, for same target map, while a vector simplification algorithm had about 13%, compression ratio in 1m resolution we confirmed our method having more than 80% encoding efficiencies about original vector map in the 1cm resolution. Also it has not only higher compression ratio but also faster computing speed than present SEC based compression algorithm through experimental results. Moreover, our algorithm presented much more high performances about accuracy and computing power than vector approximation algorithm on same data volume sizes.

A Blind Vector Digital Watermarking for GIS using the Closest Pair of Points (최근점 쌍을 이용한 벡터 맵 디지털 워터마킹)

  • Kim, Jung-Yeop;Park, Soo-Hong
    • Journal of KIISE:Information Networking
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    • v.36 no.6
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    • pp.536-544
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    • 2009
  • This paper proposed a novel vector digital watermarking method to protect copyright. The proposed method embeds watermarks after finding the closest pair of points and calculating the distance of the points. We tested the robustness of the method through several attacks on watermarked data. The experimental results show that the proposed method has more robustness than previous methods. And the new method doesn't change the topology of the vector data. Therefore, this method can be 'the vector digital watermarking for GIS.

Digital Watermarking of 2D Vector Map Data for the Accuracy and Topology of the Data (벡터 맵 데이터의 정확성과 위상을 고려한 디지털 워터마킹)

  • Kim, Junh-Yeop;Park, Soo-Hong
    • Spatial Information Research
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    • v.17 no.1
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    • pp.51-66
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    • 2009
  • There have been concerned about the copyright as numerous data are digitalized because of the growth of performance of the computer and Internet. Digital watermarking is one of strong methods to protect copyright. We proposed a novel digital watermarking for vector map data. Although vector map data are used widely in GIS, there is little interest in copyright. The proposed method is to embed and extract watermarks using CRC principle. The experimental results show that this method can protect the copyright of the vector map by extracting embedded watermarks. Therefore, the proposed method can be utilized as the technique to protect vector map data.

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A Polyline Watermarking Scheme for GIS Vector Map (GIS 벡터맵 폴리라인 워터마킹 방법)

  • Kim, Jun-Hee;Lee, Suk-Hwan;Kwon, Seong-Geun;Park, Seung-Seob;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.13 no.4
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    • pp.582-593
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    • 2010
  • Recently the commercial value of GIS(geographic information system) has been increased with growing application demands of spatial information in life space. Also, GIS has been expanded to the integrated information system that provides the ease access to map information by public users and also the combined service of GIS map data and various multimedia contents. But several security problems of GIS map data have brought up at GIS industries, such as the illegal copy and distribution of GIS map data. Furthermore, the copyright protection of GIS map data has not been researched yet compared with image and video contents. This paper presents a polyline based watermarking scheme for the copyright protection of GIS vector map. The proposed scheme analyzes the structure of vector map and embeds adaptively the watermark by using the distance distribution of polyline components. From experimental results, we verified that the proposed scheme satisfies the invisibility and the robustness of geometrical attacks.

SOM-Based $R^{*}-Tree$ for Similarity Retrieval (자기 조직화 맵 기반 유사 검색 시스템)

  • O, Chang-Yun;Im, Dong-Ju;O, Gun-Seok;Bae, Sang-Hyeon
    • The KIPS Transactions:PartD
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    • v.8D no.5
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    • pp.507-512
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    • 2001
  • Feature-based similarity has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects. the performance of conventional multidimensional data structures tends to deteriorate as the number of dimensions of feature vectors increase. The $R^{*}-Tree$ is the most successful variant of the R-Tree. In this paper, we propose a SOM-based $R^{*}-Tree$ as a new indexing method for high-dimensional feature vectors. The SOM-based $R^{*}-Tree$ combines SOM and $R^{*}-Tree$ to achieve search performance more scalable to high-dimensionalties. Self-Organizingf Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two-dimensional space. The map is called a topological feature map, and preserves the mutual relationships (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. We experimentally compare the retrieval time cost of a SOM-based $R^{*}-Tree$ with of an SOM and $R^{*}-Tree$ using color feature vectors extracted from 40,000 images. The results show that the SOM-based $R^{*}-Tree$ outperform both the SOM and $R^{*}-Tree$ due to reduction of the number of nodes to build $R^{*}-Tree$ and retrieval time cost.

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