Chaoguang Men

Nonlinear scrambling-based reversible watermarking for 2D-vector maps

The reversible watermarking technique is suitable for vector maps due to its reversibility after watermark extraction. In this paper, a novel reversible watermarking scheme based on the idea of nonlinear scrambling is proposed. It begins with feature point extraction. To avoid the high-precision vector data being illegally used by unauthorized users, the algorithm nonlinearly scrambles the relative position of feature points. Then based on the proposed reversible embedding, both scrambled feature points and nonfeature points are taken as cover data, the coordinates of which are modified to embed both watermark data and feature point identification data. Finally, combined with the scrambling secret key, the original vector data can be exactly recovered with watermark extraction. Comprehensive experimental results validate that the scheme could effectively prevent the high-precision vector data from being illegally used with maintaining the basic shape of each polyline, simultaneously.

A recursive embedding algorithm towards lossless 2D vector map watermarking

The copyright protection of two-dimensional (2D) vector map has attracted a lot of research focus due to the increasing security issues raised in recent years. One promising direction seeking the optimal tradeoff between adding watermarks and maintaining minimal distortion is the so-called lossless watermarking, i.e., after watermark extraction the 2D vector maps are fully lossless. This paper presents a novel lossless watermarking scheme for 2D vector maps based on a novel recursive embedding algorithm. In our algorithm, feature points of individual polylines are first grouped into united, upon which highly correlated unites are selected as cover data to carry out a recursive modification of its mean vertex coordinates. Such operation not only ensures lossless compression, but also enables higher payload capacity and, to a certain degree, the perception invisibility before and after the watermark extraction. We have conduced experiments on several real-world 2D vector map applications to show the effectiveness, efficiency of the proposed algorithm.

High-capacity reversible watermarking scheme of 2D-vector data

The application of two-dimensional (2D) vector map faces the security issues of copyright protection, which limit the usage of vector data in many scenarios. Reversible watermarking is a more feasible solution, which aims to restore the original data after watermark extraction. In this paper, high-capacity reversible watermarking scheme of 2D-vector data is proposed based on the idea of iterative embedding. It groups vertices as units for each polyline and selects highly correlated vertex units as cover data. Then the reversible embedding is carried out by iteratively modifying the median vertex coordinates of each selected embedding unit. This scheme can strictly recover the original vector data with watermark accurate extraction. Meanwhile, both higher payload capacity and perception invisibility are validated through theoretical analysis and comprehensive experiments. The experimental results show that the proposed reversible watermarking scheme is suitable for 2D-vector data applications where high-precision data are required.

Iterative embedding-based reversible watermarking for 2D-vector maps

Reversible watermarking aims to restore the original data after watermark extraction, which is more suitable for copyright protection of 2D-vector maps. In this paper, we present a reversible watermarking strategy for 2D-vector maps based on iterative embedding. It begins with vertex grouping of each polyline. Then only the highly correlated data sets are selected as the cover data for iterative embedding. Finally, the iterative embedding is carried out by reversibly modifying the median vertex coordinates of each selected embedding unit. The original vector data can be strictly recovered with accurate watermark extraction. Meanwhile, both higher payload capacity and better invisibility are proved through both theoretical analysis and comprehensive experimental validations. Experimental results show that the proposed reversible watermarking method is very suitable for 2D-vector map copyright protection and secret communication.

Global characteristic-based lossless watermarking for 2D-vector maps

Due to no damage to original data, the lossless watermarking is more suitable for copyright protection of vector maps. In this paper, a lossless watermarking scheme based on the global characteristics of vector map is proposed. It begins with feature point extraction of each polyline, based on which, for the extracted feature points and non-feature points, the scheme utilizes the relation model established by BP artificial neural network and the singular value decomposition (SVD) to construct the lossless watermarking parameters, respectively. Then through XOR operation between lossless parameters and copyright image, the corresponding detection keys are obtained. This scheme perfectly depicts the global characteristics of each polyline, and has complementary robustness for simplification, compression attacks and geometry attacks, achieves the comprehensive protection purpose of vector maps. Experimental results validate the complementary robustness and effective copyright distinction between different maps of the scheme. In addition, the contradiction between the robustness and imperceptibility in traditional watermarking algorithm is effectively balanced in the scheme without modifying the original vector data, so it is suitable for copyright protection of 2D-vector maps.

Performance Analysis of Rollback Recovery Schemes for the Mobile Computing Environment

Different from the wired distributed system, the mobile computing system has certain new characteristics, which impact on its checkpointing- rollback recovery schemes. The performance of these schemes primarily depends on the heterogeneous processing speeds, link bandwidth, message arrival ratio and fault rate of mobile hosts. Another special factor that should be considered is handoff which often occurs in mobile networks. New adaptations of well- known recovery schemes had been presented for the mobile environment. However the analysis shows that there is no single recovery scheme that performs well for all mobile environments. In this paper, we analysis how checkpointing and handoff schemes affect performance and effectiveness metrics, and then determine mobile environments where a particular recovery scheme is best suited. We get the optimal checkpointing interval function for minimizing the total execution time in the Logging recovery scheme. Our model allows a fault of mobile host during its recovery procedure.

Checkpoint scheduling model for optimality

To minimize the expected execution time, a general checkpoint scheduling algorithm is proposed to determine the near optimal checkpointing time sequence. More precisely, based on a simple timing policy, an execution analytical model is introduced and the expected effective ratio is derived. By maximizing the expected effective ratio, the optimal checkpoint period for the exponential failure distribution can be obtained directly, and a general checkpoint scheduling algorithm is developed to perform the near optimal checkpointing time sequence for an arbitrary failure distribution. Experimental results reveal that the proposal can perform varying checkpoint interval according to the failure distribution and the expected effective ratio of the execution is considerable for the long-running application in term of reliability.

Access-Pattern Aware Checkpointing Data Storage Scheme for Mobile Computing Environment

Abstract The rapid development of communication technology and mobile devices has facilitated the mobile computing applications such as location-based services, and information sharing. Characteristics of the mobile computing system, such as the space limitation, mobility handling, low bandwidth and limited battery life, make mobile computing applications more prone to failures. Checkpoint and rollback recovery technology, as a fault tolerance method for continuing services in mobile computing environment, is researched in this paper. Based on user access patterns, mainly considering the visit time of the mobile host(MH) to the sojourn mobile support stations (MSSs), a checkpointing data storage scheme is proposed. Only if the stay time in the current mobile support station is long enough, the mobile host should do the checkpoint and store the checkpoint data on the sojourn mobile support station. Based on the visited time to the MSS, the scheme manages checkpointing data high efficiently which is more cognitively flexible and adapt to the nomadic and mobile computing environmental conditions.

Hierarchical Routing for Large Scale Bluetooth Network

Bluetooth node is mobile and the bandwidth-limited, constructing a QoS route for communication from one node to another in scatternet is a significant challenge. A hierarchical management model can be built for large scale Bluetooth network. In this paper a hierarchical network model for Bluetooth scatternet is proposed through plotting out the flat graph into sub-graphs which are abstracted as high-level graph, and rules to partition the graph into sub-graphs is also given. Then, a shortest path calculation algorithm is given for the hierarchical network.

Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach

This paper presents a segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps. The main contribution is to integrate the appealing properties of multi-cost approach into the segmentation-based framework. Firstly, the reference image is segmented by using the mean-shift algorithm. Secondly, the initial disparity of each segment is estimated by an adaptive multi-cost method, which consists of a novel multi-cost function and an adaptive support window cost aggregation strategy. The multi-cost function increases the robustness of the initial raw matching costs calculation and the adaptive window reduces the matching ambiguity effectively. Thirdly, an iterative outlier suppression and disparity plane parameters fitting algorithm is designed to estimate the disparity plane parameters. Lastly, an energy function is formulated in segment domain, and the optimal plane label is approximated by belief propagation. The experimental results with the Middlebury stereo datasets, along with synthesized and real-world stereo images, demonstrate the effectiveness of the proposed approach.