Advanced Materials Research Vols. 989-994

Abstract: The accurate estimation of the fundamental matrix is one of the most important steps in many computer vision applications such as 3D reconstruction, camera self-calibration, motion estimation and stereo matching. In this paper, an optimal fundamental matrix estimation method based on removing exceptional match points is proposed. Firstly, the initial mismatch is reduced by the bidirectional SIFT feature matching algorithm. Secondly, the partial concentration problem of random samples is solved by the bucket segmentation method. In order to obtain robustness, the fundamental matrix is estimated in a RANSAC framework according to the principle of minimizing the geometric distance. Finally, the iterate process improves the accuracy of the fundamental matrix by using the LM algorithm. Experimental results show that the proposed method can reduce the outlier’s interference better and improve the estimation precision of the fundamental matrix.

Abstract: Application value of a variety of complex network makes it become an important scientific research challenges. Therefore, in order to more thoroughly understand the network of human life, we need to further study the properties of the complex network. Complex network search theory solves many practical problems, including the search of relationship between any two people in a social network chain.

Abstract: The Internet has gradually enters the life of people and the usage of information has become globalization gradually. It is now very common to get information through the network in day-to-day work. The Amount of data of Internet information grows in an explosive way in recent years, the huge amounts of information make it more and more difficult for users to find the information they need accurately; information overload lots problems become the great challenge of Internet development. As currently one of the most effective tool to solve the information overload, personalized recommendation technology help users filter information intelligently through the recommendation engine.

Abstract: This article first mathematical model of boiler water level, and then in MATLAB/ SIMULINK environment, the model simulation, and thus the dynamic characteristics of the model for analysis. Many real boiler parameters and variables, complex, by simplifying the modeling process, ignores some factors and variables, a simple model can be obtained results almost true fit. Boiler water level of the model established in considering the effect of steam flow and water flow of two factors.

Abstract: With the development of science and technology, people pay more and more attention to the reliability of the products, especially in some special field, such as aerospace, military products, and some products of high reliability and long life. As a part that runs through the whole life cycle of products, reliability test provides an important source of data for the design, batch production and residual life assessment of the product development. For some expensive, new products put into use, they are not quite little in amount, having the characteristics of small sample. In this case, how to use the existing data to predict product life, reliability of calculating the reliability of a product more accurately and other related parameters is particularly important.

Abstract: This paper presents a technique for adaptive ocean sampling using ocean sampling platforms equipped with multiple sensors. The virtual environment of 2D ocean sampling is established, so as to simulate the ocean sampling region by means of the sampling platforms. There are three important phases which can be written as collecting scientific data, drawing the sampling area, and utilizing the maximum differential algorithm (MDA) in ocean sampling. By analyzing the sampling data and using the maximum differential algorithm, the sampling platforms achieve the optimizing sampling path. The simulation results by adaptive ocean sampling of single sampling platform and multiple platforms show that the proposed approach is effective and feasible. This method can be applied to conduct the moving direction based on the ocean sampling platforms.

Abstract: This paper proposes a recursive least squares algorithm for Wiener systems. We use a switching function to turn the modelof the nonlinear Wiener systems into an identification model, then propose a recursive least squares identification algorithm toestimate all the unknown parameters of the systems. Finally, an example is provided to show the effectiveness of the proposed algorithm.

Abstract: In the next generation of heterogeneous wireless network environment, to meet the network requirements of diverse services ,we propose a vertical handoff decision algorithm based on QoS evaluation that refine the handover unit to services. The proposed algorithm consider the needs of the services、 network conditions、 user preferences and other factors, and makes Analytic Hierarchy Process (AHP) and cost function combine to choose the target network that is best meet the requirements of services . Comparing with the vertical handoff decision based on RSS, simulation results show that the proposed method can take full account of the different QoS requirements of various services types to choose the appropriate network, and would not cause performance degradation.

Abstract: The scrambled watermark is embedded in DCT coefficients of low-frequency sub image with the Brightness Component of original color image after lifting wavelet transformation. Before embedding the watermark, the image confusion method is used to eliminate the space correlation of the pixels and improves the security and robustness. The results showed that the algorithm is easy to carry out with the real-time request of video watermarking.

Abstract: Traditional watermark embedding introduces inevitably some perceptible quality degradation of the host image. Another problem is the inherent conflict between imperceptibility and robustness. However, the zero-watermarking technique can extract some essential characteristics from the host image and use them for watermark registration and detection. The original image was decomposed into series of multiscale and directional subimages after lifting wavelet transformation (LWT). The high order bit-plane of low-frequency subimage and watermark image are inputs of the cellular neural network (CNN), and the zero-watermarking registration image is the output. To investigate and improve the security and robustness, the original watermark and registration image are scrambled or encrypted. The watermark image can be extracted from the secret image. This algorithm is simple and robust. The proposed method is also simple for hardware realization.