Modulation of viewing angle on an LCD surface through backlight optics

Abstract— A backlight unit (BLU) that varies the viewing angle from the top to the bottom surface of a transmissive LCD screen has been developed through the design and fabrication of microstructures on a light‐guide plate (LGP). An array of taper prisms has been designed and fabricated on the back surface of the LGP, which resulted in the variation of 29° in the angular distribution of the luminance of the backlight from the top sector to the bottom sector of its surface. This characteristic is employed to modulate the viewing angle of the LCD from the top of the screen to the bottom of the screen for special applications.     

基于决策树的不完全决策表的数据补充及规则提取

不完全信息系统中遗失数据的补充和规则的提取，一直是数据挖掘技术面临的重要问题。文中给出了一种基于决策树来求解此问题的算法。对于给定的不完全决策表，该算法应用改进的ID3算法来构造决策树，在构造决策树的过程中对遗失值进行补充。对于不能在决策树上补充的遗失值，定义了一种相关对象之间的相似度来填充。该算法简单，易于操作。     

乳状液型液膜法处理含锌废水的动力学

乳状液型液膜法以其去除效果好、回收率高、处理量大、消耗低等特点，在废水治理中得到了广泛的应用。本文采用该法对含锌废水进行处理，取得了较好的效果。在此基础上，通过对分离过程动力学的研究，确定了速控步骤的动力学方程，从理论上探讨了载体和废水中锌离子浓度，以及分离温度对分离速度和分离效率的影响，并在实验中得到了验证。该动力学方程的建立，不仅为含锌废水的处理提供了依据，也为计算机模拟该过程奠定了基础。     

Natural resonance-based feature extraction with reduced aspect sensitivity for electromagnetic target classification

This paper presents a model-based electromagnetic feature extraction technique that makes use of time-frequency analysis to extract natural resonance-related target features from scattered signals. In this technique, the discrete auto-Wigner distribution of a given signal is processed to obtain a partitioned energy density vector with a significantly reduced sensitivity to aspect angle. Each partition of this vector contains, in the approximate sense, spectral distribution of the signal energy confined to a particular subinterval of time. Selection of sufficiently late-time partitions provides target features with a markedly increased target discrimination capacity. The potential of the suggested technique and the practical issues in its implementation are demonstrated by applying it to realistic target classification problems with very encouraging results.     

A new method for representing and matching shapes of natural objects

A new method for the representation and comparison of irregular two-dimensional shapes is presented. This method uses a polar transformation of the contour points about the geometric centre of the object. The distinctive vertices of the shape are extracted and used as comparative parameters to minimize the difference of contour distance from the centre. Experiments are performed, more than 39 000 comparisons of database shapes, provided by Sebastian et al. (ICCV (2001) 755), are made and the results are compared to those obtained therein. In addition, 450 comparisons of leaf shape are made and leaves of very similar shape are accurately distinguished. The method is shown to be invariant to translation, rotation and scaling and highly accurate in shape distinction. The method shows more tolerance to scale variation than that of Sebastian et al. (ICCV (2001) 755) and is less computationally intense.     

Feature extraction and dimensionality reduction algorithms and their applications in vowel recognition

Feature extraction is an important component of a pattern recognition system. It performs two tasks: transforming input parameter vector into a feature vector and/or reducing its dimensionality. A well-defined feature extraction algorithm makes the classification process more effective and efficient. Two popular methods for feature extraction are linear discriminant analysis (LDA) and principal component analysis (PCA). In this paper, the minimum classification error (MCE) training algorithm (which was originally proposed for optimizing classifiers) is investigated for feature extraction. A generalized MCE (GMCE) training algorithm is proposed to mend the shortcomings of the MCE training algorithm. LDA, PCA, and MCE and GMCE algorithms extract features through linear transformation. Support vector machine (SVM) is a recently developed pattern classification algorithm, which uses non-linear kernel functions to achieve non-linear decision boundaries in the parametric space. In this paper, SVM is also investigated and compared to linear feature extraction algorithms.     

基于复主分量分析的人脸识别

提出了一种基于复主分量分析的人脸识别新方法。首先采用两种不同的K—L变换分别降低原始图像空间的维数，得到高维原始图像的两种简约表示。然后利用复向量将同一样本的两组特征向量合并在一起，通过运用复主分量分析，来抽取人脸图像的有效鉴别特征。最后在0RL人脸库上实验结果表明所提出的方法不仅识别性能优于经典的Eigenfaces和Fisherfaces方法，而且仅用27个特征识别率就达到96％。     

噪声图像中边界提取方法的研究

在噪声图像中如何有效的提取边界是图像分析中的难点，常用的边界提取方法往往对噪声对敏感，文章针对这一情况采用了保持图像细节的多级组合滤波器先将噪声从图像中分离出来，然后再对图像进行边界提取，实验表明，该方法可以在有效的抑制噪声的同时提取出有意义的边界。     

Accessing Video Contents through Key Objects over IP

In order to support content-based video database access over the Internet Protocol (IP), achieving the following objectives are important: (i) video query by a representative object (key object) or some statistical characterization of the target contents, (ii) bandwidth-efficient browsing over IP, and (iii) scalable and user-centric video transmission over a heterogeneous and variable-bandwidth network. We present a video object extraction and scalable coding system designed to meet the above objectives. In our system, key objects of meaning to video database users are generated via a human-computer-interaction procedure, and are tracked across frames. Given a key object, an algorithm classifies a subset of its VOPs as key VOPs. This subset forms the basis of a highly bandwidth-efficient base layer for supporting activities such as browsing and refining queries. Over the base layer, a number of enhancement layers can be defined to progressively increase the spatial and temporal resolutions of retrieved video. It is expected that heterogeneous users can subscribe to different numbers of the enhancement layers according to their own conditions, such as access authorization, available connection bandwidth, and quality preference.