Local histogram based geometric invariant image watermarking

Compared with other existing methods, the feature point-based image watermarking schemes can resist to global geometric attacks and local geometric attacks, especially cropping and random bending attacks (RBAs), by binding watermark synchronization with salient image characteristics. However, the watermark detection rate remains low in the current feature point-based watermarking schemes. The main reason is that both of feature point extraction and watermark embedding are more or less related to the pixel position, which is seriously distorted by the interpolation error and the shift problem during geometric attacks. In view of these facts, this paper proposes a geometrically robust image watermarking scheme based on local histogram. Our scheme mainly consists of three components: (1) feature points extraction and local circular regions (LCRs) construction are conducted by using Harris-Laplace detector; (2) a mechanism of grapy theoretical clustering-based feature selection is used to choose a set of non-overlapped LCRs, then geometrically invariant LCRs are completely formed through dominant orientation normalization; and (3) the histogram and mean statistically independent of the pixel position are calculated over the selected LCRs and utilized to embed watermarks. Experimental results demonstrate that the proposed scheme can provide sufficient robustness against geometric attacks as well as common image processing operations. (C) 2010 Elsevier B.V. All rights reserved.

Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

construction of feature-matching perception in virtual assembly

An important characteristic of virtual assembly is interaction. Traditional di-rect manipulation in virtual assembly relies on dynamic collision detection, which is very time-consuming and even impossible in desktop virtual assembly environment. Feature-matching isa critical process in harmonious virtual assembly, and is the premise of assembly constraint sens-ing. This paper puts forward an active object-based feature-matching perception mechanism and afeature-matching interactive computing process, both of which make the direct manipulation in vir-tual assembly break away from collision detection. They also help to enhance virtual environmentunderstandability of user intention and promote interaction performance. Experimental resultsshow that this perception mechanism can ensure that users achieve real-time direct manipulationin desktop virtual environment.

Geometric Distortion Insensitive Image Watermarking in Affine Covariant Regions

Feature-based image watermarking schemes, which aim to survive various geometric distortions, have attracted great attention in recent years. Existing schemes have shown robustness against rotation, scaling, and translation, but few are resistant to cropping, nonisotropic scaling, random bending attacks (RBAs), and affine transformations. Seo and Yoo present a geometrically invariant image watermarking based on affine covariant regions (ACRs) that provide a certain degree of robustness. To further enhance the robustness, we propose a new image watermarking scheme on the basis of Seo's work, which is insensitive to geometric distortions as well as common image processing operations. Our scheme is mainly composed of three components: 1) feature selection procedure based on graph theoretical clustering algorithm is applied to obtain a set of stable and nonoverlapped ACRs; 2) for each chosen ACR, local normalization, and orientation alignment are performed to generate a geometrically invariant region, which can obviously improve the robustness of the proposed watermarking scheme; and 3) in order to prevent the degradation in image quality caused by the normalization and inverse normalization, indirect inverse normalization is adopted to achieve a good compromise between the imperceptibility and robustness. Experiments are carried out on an image set of 100 images collected from Internet, and the preliminary results demonstrate that the developed method improves the performance over some representative image watermarking approaches in terms of robustness.

人工神经网络在植被遥感影像分类中的应用研究

比起传统的统计方法，人工神经网络具有很好的非线性处理和并行计算能力，在植被遥感信息处理中得到广泛的应用。本研究系统地介绍了人工神经网络理论及其在植被遥感信息处理中的应用现状。并就如何提高人工神经网络的相干被遥感影像的分类能力进行了详细研究。首次提出了结合植被指数和组成分分析的神经网络分类方法。过去这方面的研究工作大都集中在通过选择一个合适的神经网络模型来提高植被分类精度，而我们认为：根据植被遥感自身的规律，结合统计方法，确定合适的网络输入模式的特征变量，也可以提高分类精度。 研究结果表明，尽管一般的神经网络分类器不需要对输入的模式做明显的特征提取，网络的隐层就具有特征提取的功能。但对TM影像七个波段和常用的五个植被指数（PVI、NDVI、WDVI、PVI、MSAVI2），分别做主成分分析，从而获得人工神经网络输入的特征变量，使用这样一种结合VI、PCA的神经网络对遥感TM多波段影像进行植被分类，能大大提高分类的精度。

基于QoS的Pareto最优的服务选择

随着越来越多的服务能够满足用户的功能需求,需要一种策略基于服务的多种QoS属性来帮助用户选择合适的服务。以XML描述服务的QoS属性,提出了一种基于QoS的Pareto最优的服务选择策略,选择出那些不在所有的QoS属性上劣于其它服务的服务。实验结果表明,与随机选择和偏好导向的选择策略相比,Pareto最优策略有独特的效果。

支持服务关联的组合服务选择方法研究

在面向服务的应用中，服务集成商通过选择已有服务并对这些服务进行组合，为其消费者提供增值（value—added）服务．然而，现有的组合服务选择模型中，各可选服务被认为是相互独立的，可选服务的服务质量独立于其他服务．而在实际的面向服务应用中，可选服务的服务质量往往依赖于其他可选服务，现有组合服务选择方法无法应对这种普遍存在的场景．文中提出了一个支持服务关联关系的QoS描述模型，用于刻画可选服务的服务质量对其他可选服务的依赖关系，并给出该QoS描述的自动生成方法．在此基础上，提出了支持服务关联的组合服务选择方法，包括基于整数规划求解最优解的组合服务选择方法和基于启发求解次优解的组合服务选择方法．通过实例分析，体现了文中方法具有良好的适用性．对比实验结果表明，文中基于整数规划方法获取的组合服务QoS明显优于同类方法；并且，文中基于启发式方法能够高效地获取较优组合服务QoS．

濮城油田沙三中6-10高分辨率层序地层学研究

The foundation of reservoir model and residual oil prediction have been the core of reservoir detailed description for improved oil production and enhanced oil recovery. The traditional way of sandstone correlation based on the geometrical similarity of well-logs which emphasizes "based on the cycle and correlating from larger to smaller" has shown its theoretical limits when explaining the correlating and the scale, geometry, continuity, connectivity of sandstones and the law of the reservoir property. It has been an urgent and difficult subject to find new theory and methods to solve the reservoir correlation and property prediction. It's a new way to correlate strata and found framework of reservoir through the process-response analysis in the base-level cycles. And it is also possible to analyze the reservoir property in reservoir framework. Taking the reservoir of zonation 6-10 in S3~2 of Pucheng Oil Field in Henan Province as an example, we founded the detailed reservoir stratigraphic framework through base-level correlation. In the strata frame, sediment distribution and its development are discussed based on sediment volume partitioning and facies differentiation analysis. Reservoir heterogeneities and its relation to base-level are also discussed. The analysis of primary oil distribution shows the base-level controlled oil distribution in reservoir. In this paper, subjects as following are discussed in detail. Based on the analysis of sedimentary structure and sedimentary energy, the facies model was founded. Founding stratigraphy framework through base level analysis In the studying zone, one long term cycle, 6 middle term cycles and 27 short term cycles was identified and correlated. 3 Predicting the property of reservoir for improving oil development The base level controlled the property of sandbody. The short and very short term cycle controlled the pattern of heterogeneities in sandbody, and the middle and long term cycle controlled the area and inter-layer heterogeneities. On the lower location of the middle and long term base level, the sandbody is well developed, with a wide area and large thickness, while on the high location of base level, there is an opposite reservoir character. 4 The studying of reservoir development response and oil distribution making a solid base for development adjustment Primary oil distribution is controlled by base level location. It tells that the sandbody on the high base level location was poor developed for its difficulty to develop. While on the low location of the base level, the sandbody is well developed for its relative easy to develop and dominant role in the development, but high residual oil for its high original oil content.

Weighted least-squares phase unwrapping algorithm based on derivative variance correlation map

Among different phase unwrapping approaches, the weighted least-squares minimization methods are gaining attention. In these algorithms, weighting coefficient is generated from a quality map. The intrinsic drawbacks of existing quality maps constrain the application of these algorithms. They often fail to handle wrapped phase data contains error sources, such as phase discontinuities, noise and undersampling. In order to deal with those intractable wrapped phase data, a new weighted least-squares phase unwrapping algorithm based on derivative variance correlation map is proposed. In the algorithm, derivative variance correlation map, a novel quality map, can truly reflect wrapped phase quality, ensuring a more reliable unwrapped result. The definition of the derivative variance correlation map and the principle of the proposed algorithm are present in detail. The performance of the new algorithm has been tested by use of a simulated spherical surface wrapped data and an experimental interferometric synthetic aperture radar (IFSAR) wrapped data. Computer simulation and experimental results have verified that the proposed algorithm can work effectively even when a wrapped phase map contains intractable error sources. (c) 2006 Elsevier GmbH. All rights reserved.

tilt menu: using the 3d orientation information of pen devices to extend the selection capability of pen-based user interfaces

We present a new technique called‘Tilt Menu’ for better extending selection capabilities of pen-based interfaces.The Tilt Menu is implemented by using 3D orientation information of pen devices while performing selection tasks.The Tilt Menu has the potential to aid traditional onehanded techniques as it simultaneously generates the secondary input (e.g., a command or parameter selection) while drawing/interacting with a pen tip without having to use the second hand or another device. We conduct two experiments to explore the performance of the Tilt Menu. In the first experiment, we analyze the effect of parameters of the Tilt Menu, such as the menu size and orientation of the item, on its usability. Results of the first experiment suggest some design guidelines for the Tilt Menu. In the second experiment, the Tilt Menu is compared to two types of techniques while performing connect-the-dot tasks using freeform drawing mechanism. Results of the second experiment show that the Tilt Menu perform better in comparison to the Tool Palette, and is as good as the Toolglass.

基于克隆选择算法的非线性优化迭代学习控制；Clonal selection algorithm based nonlinear optimal iterative learning control

为实现对模型不确定的有约束非线性系统在特定时间域上输出轨迹的有效跟踪,将改进的克隆选择算法用于求解迭代学习控制中的优化问题。提出基于克隆选择算法的非线性优化迭代学习控制。在每次迭代运算后,一个克隆选择算法用于求解下次迭代运算中的最优输入,另一个克隆选择算法用于修正系统参考模型。仿真结果表明,该方法比GA-ILC具有更快的收敛速度,能够有效处理输入上的约束以及模型不确定问题,通过少数几次迭代学习就能取得满意的跟踪效果。

Local Feature Based Geometric-Resistant Image Information Hiding

Watermarking aims to hide particular information into some carrier but does not change the visual cognition of the carrier itself. Local features are good candidates to address the watermark synchronization error caused by geometric distortions and have attracted great attention for content-based image watermarking. This paper presents a novel feature point-based image watermarking scheme against geometric distortions. Scale invariant feature transform (SIFT) is first adopted to extract feature points and to generate a disk for each feature point that is invariant to translation and scaling. For each disk, orientation alignment is then performed to achieve rotation invariance. Finally, watermark is embedded in middle-frequency discrete Fourier transform (DFT) coefficients of each disk to improve the robustness against common image processing operations. Extensive experimental results and comparisons with some representative image watermarking methods confirm the excellent performance of the proposed method in robustness against various geometric distortions as well as common image processing operations.