• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6190-6213
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• 2019

For small-scale vector data, restrictions on watermark scheme capacity and robustness limit the use of copyright protection. A watermarking scheme based on robust geometric features and capacity maximization strategy that simultaneously improves capacity and robustness is presented in this paper. The distance ratio and angle of adjacent vertices are chosen as the watermark domain due to their resistance to vertex and geometric attacks. Regarding watermark embedding and extraction, a capacity-improved strategy based on quantization index modulation, which divides more intervals to carry sufficient watermark bits, is proposed. By considering the error tolerance of the vector map and the numerical accuracy, the optimization of the capacity-improved strategy is studied to maximize the embedded watermark bits for each vertex. The experimental results demonstrated that the map distortion caused by watermarks is small and much lower than the map tolerance. Additionally, the proposed scheme can embed a copyright image of 1024 bits into vector data of 150 vertices, which reaches capacity at approximately 14 bits/vertex, and shows prominent robustness against vertex and geometric attacks for small-scale vector data.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.359-366
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• 2003

Although the reuse of the cached data for scrolling the map reduces the amount of passed data between client and server, it needs the conversions of data coordinates, selective deletion of objects, cache compaction and object structuring step in the clients. The conversion is a time- intensive operation due to limited resources of mobile phones such as low computing power, small memory. Therefore, in order to control the map efficiently in the vector map service based mobile phones, it is necessary to study the methods which reuse cached objects for reducing wireless network bandwidth and overwhelming the limited resources of mobile phones as well. This paper proposes the methods of reusing pre-received spatial objects for map control in the mobile vector map service system based on client-server architecture. The experiments conducted on the Web GIS systems with real data show that the proposed method is appropriate to map services for mobile phone. We also analyze the advantages and drawbacks between the reuse of cached data and transmission of raw data respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.464-467
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• 2003

There are two approaches to construct mobile GIS, Vector and Raster methods, according to the map data transformation format from server to mobile client. Each method requires a different implementation architecture of server and client modules for mobile map services. And each have advantages and disadvantages at the different aspects. This thesis implements these two approaches, thus, compares the each merits, by experiments. They include the transmission performance, map quality, and so on.

• 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 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.

• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.131-138
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• 2015

In this paper, we propose L1-norm regularization for state vector adaptation of subspace Gaussian mixture model (SGMM). When you design a speaker adaptation system with GMM-HMM acoustic model, MAP is the most typical technique to be considered. However, in MAP adaptation procedure, large number of parameters should be updated simultaneously. We can adopt sparse adaptation such as L1-norm regularization or sparse MAP to cope with that, but the performance of sparse adaptation is not good as MAP adaptation. However, SGMM does not suffer a lot from sparse adaptation as GMM-HMM because each Gaussian mean vector in SGMM is defined as a weighted sum of basis vectors, which is much robust to the fluctuation of parameters. Since there are only a few adaptation techniques appropriate for SGMM, our proposed method could be powerful especially when the number of adaptation data is limited. Experimental results show that error reduction rate of the proposed method is better than the result of MAP adaptation of SGMM, even with small adaptation data.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.229-235
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• 2024

Recent years have seen active research on methods for efficiently processing and interpreting large volumes of data in the fields of artificial intelligence and machine learning. One of these data processing technologies, Vector Symbolic Architecture (VSA), offers an innovative approach to representing complex symbols and data using high-dimensional vectors. VSA has garnered particular attention in various applications such as natural language processing, image recognition, and robotics. This study quantitatively evaluates the characteristics and performance of VSA methodologies by applying five VSA methodologies to the MNIST dataset and measuring key performance indicators such as encoding speed, decoding speed, memory usage, and recovery accuracy across different vector lengths. BSC and VT demonstrated relatively fast performance in encoding and decoding speeds, while MAP and HRR were relatively slow. In terms of memory usage, BSC was the most efficient, whereas MAP used the most memory. The recovery accuracy was highest for MAP and lowest for BSC. The results of this study provide a basis for selecting appropriate VSA methodologies depending on the application area.

• 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.

• 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.