Anbo Li

Data quality inspection of watermarked GIS vector map

In recent years, digital watermarking is playing an increasingly important role in the geographical information copyright protection. According to the characteristics of GIS vector data, the watermark embedding algorithms should at least meet the following demands: no significant loss in data accuracy, no obvious reduction in data quality and no significant change in visual observation. In this paper, the quality of watermarked GIS vector data is inspected through polygon closure, data topology, error analysis and visual analysis. And the above functions are achieved by coding. Through experiments we can find that this method can inspect the quality of watermarked GIS vector data well, so that it can provide basis for judging whether the watermark embedding algorithm is good.

Review on Copyright Marking Techniques of GIS Vector Data

The copyright of GIS vector data has become an increasingly complex topic. The main technologies used for copyright protection is the copyright marking techniques delegated by watermarking. In this paper, the current status and future prospects of copyright marking techniques of GIS vector data is summarized from basic theory, marking generating, marking embedding, marking detection and real-time monitoring.

Copyright protection for GIS vector data production

Limited by the characters of GIS vector data, such as variety and complexity of expression, universality, mass, disorder and pretty good privacy, etc., the traditional copyright protection methods for image and audio productions cannot be applied into GIS vector data productions directly. In this paper, a solution to copyright protection of GIS vector data productions is proposed. Firstly, information characteristics, data organization and storage characteristics and attack characteristics of GIS vector data are comprehensively analyzed. Secondly, based on hash, file filter driver, dynamic encryption and decryption, the key techniques including zero-watermarking generation, access control, and data content protection are described. Finally, a copyright protection frame of GIS vector data is put forward.

Study on benchmark system for copyright marking algorithms of GIS vector data

GIS vector data is widely used in economic construction, social life, management decision, military affairs, et al. The application of GIS vector data faces some unsolved issues such as digital copyright protecting, data authenticating, and data source tracing, etc. These issues could be obstacles restricting the further usage of digital vector data. The illegally forged, distributed or tampered data could pose a threat to the healthy development of geography information industry. With the increasing of copyright problems, copyright protection of GIS vector data has been drawing more and more attention. The technique of watermarking provides potential solutions for the problem. Comparing with the watermarking schemes designed for general multimedia data, watermarking GIS vector data has some distinct features due to the special data structures and application environments of GIS vector data. The special organization and storage characteristics of GIS vector data makes it difficult to simply apply existing copyright marking techniques to GIS vector data. Some research and applications have been done on copyright marking techniques of GIS vector data, mainly about basic theory, marking generation, marking embedding and marking detection. Today, the GIS watermarking community needs some advanced attacks and fair benchmarks in order to compare the performances of different copyright marking algorithms of GIS vector data. Study on Benchmark System for copyright marking algorithms of GIS vector data permit to find the weaknesses of an algorithm and consequently trigger further research in order to overcome the problem. In this paper, firstly, the construction of benchmark dataseis is studied from two aspects of data source and data organization. Secondly, some attacks of GIS vector data watermarking is analyzed and the automated benchmark method for watermarking performances based on simulated attacks is proposed. Lastly, the system architecture of benchmark system for copyright marking algorithms of GIS vector data is presented.

GIS vector data automatic watermark detection based on mobile agent technology

Digital watermarking is an effective technology for copyright protection, but the passive of traditional detection method limits the application of this technology for vector data in GIS. Mobile agent technology, which is a combination of artificial intelligence technology and network technology, has some obvious advantages that could solve this problem. This paper studies mobile agent technology, and then presents a mobile agent-based automatic digital watermark detection method for vector data, finally a prototype system is developed adopting the Aglet platform.

Research of robustness evaluation method for GIS vector data digital watermarking algorithm

Digital watermark technology of GIS vector data consists of designing the digital watermark algorithm and evaluating the digital watermark algorithm performance, also, robustness is a most important evaluation indicator of the digital watermark algorithm performance, therefore, this article focuses on evaluating the robustness of digital watermark algorithm of GIS vector data.

Study on the method of cartographic visualization quality automated testing

For a long time, cartographers pay more attention to the quality control at the aspects of accuracy, logical consistency and completeness of cartographic geometry data. However, they ignored the theory and the research on the method of quality control at the aspects of aesthetics and visibility of map. For further research and application, the paper studies on the representation method of the cartographic knowledge based on RuleML and rules technology based on NXBRE forming the research on the method of cartographic visualization quality automated testing. The batch testing on pieces of maps shows that errors or omissions do not exist and the test result consistent with the actual situation.