• 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.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.964-969
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• 2007

In this paper, we propose the image watermarking method for good compression ratio and satisfactory image quality of the cover image and the embedding image. This method is based on the singular value decomposition and the vector quantization using fuzzy c-mean clustering. Experimental results show that the embedding image has invisibility and robustness to various serious attacks. The advantage of this watermarking method is that we can achieve both the compression and the watermarking method for the copyright protection simultaneously.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.513-520
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• 2005

In this paper, we propose a robust multi-watermarking method based on vector quantization using an index transform function. In contrast with the conventional watermark embedding methods to embed only one watermark at a time into the original image, we present a method to embed multiple watermarks for copyright protection. The proposed method efficiently enhances the robustness by index transform function which minimizes changes of vector quantization indices against various attacks. Experimental results show that the proposed method has a good robustness against various attacks compared with the conventional multi-watermarking method based on vector quantization.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.37-44
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• 2009

Digital watermarking is a technology for preventing illegal copying, for protecting intellectual property rights and copyrights, and for suggesting grounds of the ownership by inserting watermarks into digital contents. Generally speaking, watermarking techniques cannot escape from data distortion and quality degradation due to the watermark insertion. In order to overcome the shortcoming, zero-watermarking techniques which do not change the original data have been proposed recently. This paper proposes CSMVQ(Chaotic SMVQ), a zero-watermarking system for SMVQ(Side Match Vector Quantization) which shows better compression ratio and quality and less blocking effect than VQ(Vector Quantization). In SMVQ, compression progresses from left top to right bottom in order to use the information of the two neighbor blocks, so it is impossible to insert watermarks chaotically. In the process of encoding, CSMVQ dynamically considers the information of the (1 to 4) neighbor blocks already encoded. Therefore, watermark can be inserted into digital contents in chaotic way. Experimental results show that the image quality compressed by CSMVQ is better than that of SMVQ and the inserted watermark is robust against some common attacks.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.393-400
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• 2005

Due to the development of the network and Internet, it is easy to copy and spread digital data. These data has the advantage of being able to be copy without loss. However, this has generated a problem over copyright. The problem occurred in GIS, too. Although GIS data acquisition is the major cost there is insufficient effort made to protect copyright. For this reason watermarking could be a good method to guarantee owner's copyright. This paper will explain watermarking, and show an overview of watermarking studies connecting image and vector data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3475-3496
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• 2018

Most of current watermarking algorithms for GIS vector data embed copyright information by means of modifying the coordinate values, which will do harm to its quality and accuracy. To preserve the fidelity of vector line data and protect its copyright at the same time, a lossless watermarking algorithm is proposed based on storage feature in this paper. Firstly, the superiority of embedding watermark based on storage feature is demonstrated theoretically and technically. Then, the basic concepts and operations on storage feature have been defined including length and angle of the polyline feature. In the process of embedding watermark, the watermark information is embedded into directions of polyline feature by the quantitative mechanism, while the positions of embedding watermark are determined by the feature length. Hence, the watermark can be extracted by the same geometric features without original data or watermark. Finally, experiments have been conducted to show that coordinate values remain unchanged after embedding watermark. Moreover, experimental results are presented to illustrate the effectiveness of the method.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.796-798
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• 2001

본 논문에서는 벡터 양자화(Vector Quantization)를 이용해서 소유자의 저작물에 대해 저작권을 보호할 수 있는 디지털 워터마킹(Watermarking) 기법을 제안한다. 소유자의 워터마크 정보로는 사용자 정보를 비밀키를 이용해서 암호화한 데이터를 사용하며, 워터마킹 처리는 원본 이미지를 웨이블렛 기반의 벡터 양자화(Vector Quantization)에 사용되는 코드북(Coodbook)을 이용한다. 코드북을 사용함으로서 양질의 정보를 유지하면서 워터마킹을 효과적으로 처리할 수 있다.

• Spatial Information Research
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• v.15 no.4
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• pp.385-395
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• 2007

As the growth of performance of the computer and the development of the Internet are exponential, sharing and using the information illegally have also increased to the same proportion. In this paper, we proposed a novel method on the vector map data among digital contents. Vector map data are used for GIS, navigation and web-based services etc. We embedded watermark into the coordinate of the vector map data using bit operation and extracted the watermark. This method helps to protect the copyright of the vector map data. This watermarking method is a spatial domain method and it embeds the watermark within an allowable error. Our experiment shows that the watermark produced by this method is resistant to simplification and translation.

• 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.