• Journal of Multimedia Information System
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• v.4 no.4
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• pp.249-254
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• 2017

Digital vector maps must be compressed effectively for transmission or storage in Web GIS (geographic information system) and mobile GIS applications. This paper presents a polyline compression method that consists of polyline feature-based hybrid simplification and second derivative-based data compression. Experimental results verify that our method has higher simplification and compression efficiency than conventional methods and produces good quality compressed maps.

• 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.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.298-311
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• 2015

Vector data represents a map by its coordinate and Raster data represents a map by its pixel. Since these data types have very large data size, data compression procedure is a compulsory process. This paper compare the results from three different methodologies; GIS (Geographic Information System) vector map data compression using DP(Douglas-Peucker) Simplification algorithm, vector data compression based on Bin classification and the combination between two previous methods. The results shows that the combination between the two methods have the best performance among the three tested methods. The proposed method can achieve 4-9% compression ratio while the other methods show a lower performance.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1253-1258
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• 2006

In the mobile vector map service environments, there are problems like as terminal resource shortage and transmission delay for the characteristics of large spatial data. For the normal mobile vector map services, some techniques are required to overcome the problems. Spatial data compression approach is one of the techniques to reduce the bandwidth and the waiting time at clients. However it also must be considered that the effect on total efficiency caused by the overhead of compression and restoration time. This thesis proposes two spatial data compression techniques. First approach is to get relative coordinates to first coordinate of each object. The other approach is to compute client coordinates before transmission. Through the implementation and experiments, proposed techniques are evaluated the compression effects and efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.358-362
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• 2004

According to the rapid advance of computer and communication techniques, the request of mobile internet services is highly increasing. However, the main obstacles for mobile vector map service environments, are large data volume and narrow wireless bandwidth. Among the many possible solutions, spatial data compression technique may contribute to reduce the load of bandwidth and client response time. This thesis proposes two methods for spatial data compression. The one is relative coordinates transformation method, and the other is client coordinates transformation method. And, this thesis also proposes the system architecture for experiments. The two compression methods could be evaluated the compression effect and the response time.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.950-954
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• 2004

According to the rapid advance of computer and communication techniques, the request of mobile internet services is highly increasing. However, the main obstacles for mobile vector map service environments, are large data volume and narrow wireless bandwidth. Among the many possible solutions, spatial data compression technique may contribute to reduce the load of bandwidth and client response time. This thesis proposes two methods for spatial data compression. The one is relative coordinates transformation method, and the other is client coordinates transformation method. And, this thesis also proposes the system architecture for experiments. The two compression methods could be evaluated the compression effect and the response time.

• 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.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.355-364
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• 2005

Vector data sets (e.g. maps) are currently major sources of displaying, querying, and identifying locations of spatial features in a variety of applications. Especially in mobile environment, the needs for using spatial data is increasing, and the relative large size of vector maps need to be smaller. Recently, there have been several studies about vector map compression. There was clustering-based compression method with novel encoding/decoding scheme. However, precedent studies did not consider that spatial data have to be updated periodically. This paper explores the problem of existing clustering-based compression method. We propose an adaptive approximation method that is capable of handling data updates as well as reducing error levels. Experimental evaluation showed that when an updated event occurred the proposed adaptive approximation method showed enhanced positional accuracy compared with simple cluster based compression method.