Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

Document recommendation for knowledge sharing in personal folder environments

Sharing sustainable and valuable knowledge among knowledge workers is a fundamental aspect of knowledge management. In organizations, knowledge workers usually have personal folders in which they organize and store needed codified knowledge (textual documents) in categories. In such personal folder environments, providing knowledge workers with needed knowledge from other workers’ folders is important because it increases the workers’ productivity and the possibility of reusing and sharing knowledge. Conventional recommendation methods can be used to recommend relevant documents to workers; however, those methods recommend knowledge items without considering whether the items are assigned to the appropriate category in the target user’s personal folders. In this paper, we propose novel document recommendation methods, including content-based filtering and categorization, collaborative filtering and categorization, and hybrid methods, which integrate text categorization techniques, to recommend documents to target worker’s personalized categories. Our experiment results show that the hybrid methods outperform the pure content-based and the collaborative filtering and categorization methods. The proposed methods not only proactively notify knowledge workers about relevant documents held by their peers, but also facilitate push-mode knowledge sharing.     

Global Intrinsic Symmetries of Shapes

Although considerable attention in recent years has been given to the problem of symmetry detection in general shapes, few methods have been developed that aim to detect and quantify the intrinsic symmetry of a shape rather than its extrinsic, or pose‐dependent symmetry. In this paper, we present a novel approach for efficiently computing symmetries of a shape which are invariant up to isometry preserving transformations. We show that the intrinsic symmetries of a shape are transformed into the Euclidean symmetries in the signature space defined by the eigenfunctions of the Laplace‐Beltrami operator. Based on this observation, we devise an algorithm which detects and computes the isometric mappings from the shape onto itself. We show that our approach is both computationally efficient and robust with respect to small non‐isometric deformations, even if they include topological changes.     

Geometric rectification of camera-captured document images

Compared to typical scanners, handheld cameras offer convenient, flexible, portable, and non-contact image capture, which enables many new applications and breathes new life into existing ones. However, camera-captured documents may suffer from distortions caused by non-planar document shape and perspective projection, which lead to failure of current OCR technologies. We present a geometric rectification framework for restoring the frontal-flat view of a document from a single camera-captured image. Our approach estimates 3D document shape from texture flow information obtained directly from the image without requiring additional 3D/metric data or prior camera calibration. Our framework provides a unified solution for both planar and curved documents and can be applied in many, especially mobile, camera-based document analysis applications. Experiments show that our method produces results that are significantly more OCR compatible than the original images.     

Real-time modeling and rendering of raining scenes

Real-time modeling and rendering of a realistic raining scene is a challenging task. This is because the visual effects of raining involve complex physical mechanisms, reflecting the physical, optical and statistical characteristics of raindrops, etc. In this paper, we propose a set of new methods to model the raining scene according to these physical mechanisms. Firstly, by adhering to the physical characteristic of raindrops, we model the shapes, movements and intensity of raindrops in different situations. Then, based on the principle of human vision persistence, we develop a new model to calculate the shapes and appearances of rain streaks. To render the foggy effect in a raining scene, we present a statistically based multi-particles scattering model exploiting the particle distribution coherence along each viewing ray. By decomposing the conventional equations of single scattering of non-isotropic light into two parts with the physical parameter independent part precalculated, we are able to render the respective scattering effect in real time. We also realize diffraction of lamps, wet ground, the ripples on puddles in the raining scene, as well as the beautiful rainbow. By incorporating GPU acceleration, our approach permits real-time walkthrough of various raining scenes with average 20 fps rendering speed and the results are quite satisfactory.     

两种近似EMD的图像检索方法

相似度量是图像检索的关键,EMD是一种有效的度量距离,但其计算比较复杂,而且赖于基本距离的选择。采用Lloyd聚类算法对图像进行高斯混合建模,并以聚类失真作为基本距离提出了两种近似EMD的方法计算相似度。实验结果验证了该方法的有效性,其检索效率与EMD方接近,而且计算复杂度比EMD方法低,基本距离的选择不敏感。     

基于AD698的半桥式电感位移传感器高灵敏度测量电路设计

针对主动磁轴承系统中电感位移传感器的高灵敏度设计要求,在对AD698芯片的输入输出特性进行了实验测量的基础上,对AD698的典型应用电路加以改进,提出了一种基于AD698的半桥式电感位移传感器高灵敏度测量电路设计方案。实验证明,相对于AD698的典型应用电路,这种方案能够显著地提高电路的灵敏度,并且输出电压的噪声没有明显增大。     

采用UC3844的反激式开关电源反馈回路的改进与设计

介绍了一种基于PWM控制芯片UC3844的反激式开关电源的反馈回路改进设计,详细讨论了新型反馈电路的工作过程及设计方案,采用光耦PC817和电压基准TL431组成反馈网络。该电源性能优良,具有结构简单,稳压效果好,负载调整率高等优点,具有很高的生产应用价值。     

An improved NEH-based heuristic for the permutation flowshop problem

NEH is an effective heuristic for solving the permutation flowshop problem with the objective of makespan. It includes two phases: generate an initial sequence and then construct a solution. The initial sequence is studied and a strategy is proposed to solve job insertion ties which may arise in the construct process. The initial sequence which is generated by combining the average processing time of jobs and their standard deviations shows better performance. The proposed strategy is based on the idea of balancing the utilization among all machines. Experiments show that using this strategy can improve the performance of NEH significantly. Based on the above ideas, a heuristic NEH-D (NEH based on Deviation) is proposed, whose time complexity is O(mn²), the same as that of NEH. Computational results on benchmarks show that the NEH-D is significantly better than the original NEH.