基于降维LBP与叶片形状特征的植物叶片识别方法

为解决由于植物叶片特征的相似性以及叶片旋转导致植物识别率较低的问题,提出一种基于降维局部二值模式（LBP）与叶片形状特征相结合的植物叶片识别方法。首先利用LBP算法提取高维叶片纹理信息,通过主成分分析方法（PCA）对高维叶片特征降维;同时考虑叶片的形状特征,将LBP旋转不变性特征与叶片形状特征有效结合,在低维空间利用k近邻法（KNN）实现叶片的分类与识别。实验结果表明该方法具有较好的识别效果。     

Fuzzy tree automata and syntactic pattern recognition

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ?-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ?-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,' ``approximate elongated isosceles triangle,' ``approximate rectangle,' and ``approximate cross' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,' ``houses with high roofs,' and ``fuzzy churches,' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.     

Applicability of pattern recognition techniques to the analysis of urban quality from satellites

The information available in space imagery (Apollo, ERTS, etc.) of urban features is perishable. Near-real time extraction and application of urban quality information from space imagery is important in the light of the perishability of these types of data. Automated pattern recognition and classical photointerpretation methods are relevant to that problem.

Initial efforts currently under way at Allied Research Associates, Inc., Earth Resource Analysis Center, are directed toward development of techniques for:

1. a. Urban quality analysis through spatial density evaluation.

2. b. Analysis of urban quality through Fourier transforms of space imagery.

Future application of hardwired Fourier operators mounted on the spacecraft and operating on imagery transforms could provide data compression, thereby reducing the burden imposed on the down-link, and permit near-real time application of the reduced data to various user-oriented decision models.     

An evaluation of self-adjusting binary search tree techniques

Much has been said in praise of self-adjusting data structures, particularly self-adjusting binary search trees. Self-adjusting trees are most suited to skewed key-access distributions as the techniques attempt to place the most commonly accessed keys near the root of the tree. Theoretical bounds on worst-case and amortized performance (i.e. performance over a sequence of operations) have been derived which compare well with those for optimal binary search trees. In this paper, we compare the performance of three different techniques for self-adjusting trees with that of AVL and random binary search trees. Comparisons are made for various tree sizes, levels of key-access-frequency skewness and ratios of insertions and deletions to searches. The results show that, because of the high cost of maintaining self-adjusting trees, in almost all cases the AVL tree outperforms all the self-adjusting trees and in many cases even a random binary search tree has better performance, in terms of CPU time, than any of the self-adjusting trees. Self-adjusting trees seem to perform best in a highly dynamic environment, contrary to intuition.     

Unnatural pattern recognition on control charts using correlation analysis techniques

This paper presents analysis and development of a pattern recognition system for identifying unnatural patterns on quality control charts. The system is based on correlation analysis, where a set of optimal matched filters are generated. To illustrate the design methodology and operation of the system, a set of commonly encountered patterns is utilized, such as the trend, the systematic, and the cyclic patterns. A training algorithm that minimizes the probabilities of Type I and Type II errors is presented. To evaluate the system performance, a testing algorithm as well as a set of newly-defined performance measures are introduced. The obtained results have shown the effectiveness of correlation analysis for control chart pattern recognition.     

Applications of approximate string matching to 2D shape recognition

A new method for the recognition of arbitrary two-dimensional (2D) shapes is described. It is based on string edit distance computation. The recognition method is invariant under translation, rotation, scaling and partial occlusion. A set of experiments are described demonstrating the robustness and reliability of the proposed approach.     

RBPN在模式识别研究中的应用

基于RBF(radialbasisfunction)网络和感知器 (perceptron)网络建立起一种新型四层前向神经网络———径向基感知器网络 (RBPN, radialbasisperceptronnetwork). 该网络主要有以下特点 :1)网络结构上, 两层隐层选择性连接 ;2 )学习规则上, 采用同时考虑输入输出样本信息的IOC(input outputclustering)聚类方法且聚类中心的形状参数σ自适应变化. 对材料成分分析领域的仿真结果表明, 该网络可成功地包含材料成分的构成信息,     

Face recognition by decision fusion of two-dimensional linear discriminant analysis and local binary pattern

To investigate the robustness of face recognition algorithms under the complicated variations of illumination, facial expression and posture, the advantages and disadvantages of seven typical algorithms on extracting global and local features are studied through the experiments respectively on the Olivetti Research Laboratory database and the other three databases (the three subsets of illumination, expression and posture that are constructed by selecting images from several existing face databases). By taking the above experimental results into consideration, two schemes of face recognition which are based on the decision fusion of the two-dimensional linear discriminant analysis (2DLDA) and local binary pattern (LBP) are proposed in this paper to heighten the recognition rates. In addition, partitioning a face non-uniformly for its LBP histograms is conducted to improve the performance. Our experimental results have shown the complementarities of the two kinds of features, the 2DLDA and LBP, and have verified the effectiveness of the proposed fusion algorithms.     

LBP与LNMF特征融合的人脸识别

提出一种融合局部二值模式(LBP)和局部非负矩阵分解(LNMF)进行人脸识别的方法,采用LBP算子提取分块人脸图像的LBP直方图序列(LBPHS),根据每块的贡献度,得到权重的直方图序列(WeightLBPHS),采用LNMF方法提取其非负子空间及其系数矩阵,根据最近邻原则进行识别。在ORL和YALE标准人脸数据库上的实验表明,该方法具有较高的识别率。     

基于二叉树和Adaboost算法的纸币号码识别

运用一种快速弱分类器训练算法和高速缓存策略来加速Adaboost算法的训练。集成学习算法Adaboost能够精确构建二分类器,运用二叉树型结构快速灵活地将纸币号码识别转化为一系列的Adaboost二分类问题。实验结果证明, 快速Adaboost训练算法能加快训练速度,基于二叉树和Adaboost的纸币号码识别系统具有较好的识别率和处理速度,已经应用在点钞机、清分机和ATM中。     

非采样Contourlet变换与局部二值模式相结合的人脸识别

针对人脸识别中姿态、光照和表情变化带来的识别率有限的问题,提出了一种基于非采样Contourlet变换(NSCT)与局部二值模式（LBP）的人脸特征提取方法。首先对人脸图像进行非采样Contourlet变换,得到多尺度、多方向的子带系数矩阵,然后利用LBP算子从每个子带系数矩阵上抽取局部邻域关系,得到各子带的LBP特征图谱,最后将这些图谱分块统计并级联后作为人脸的识别特征。利用多通道最近邻分类器的分类结果表明,所提方法能有效提高识别率,所提取的特征对光照、表情和姿态等变化具有更好的鲁棒性。     

基于局部二值模式和深度学习的人脸识别

针对人脸识别中深度学习直接提取人脸特征时忽略了其局部结构特征的问题,提出一种将分块局部二值模式(LBP)与深度学习相结合的人脸识别方法.首先,将人脸图像分块,利用均匀LBP算子分别提取图像各局部的LBP直方图特征,再按照顺序连接在一起形成整个人脸的LBP纹理特征; 其次,将得到的LBP特征作为深度信念网络(DBN)的输入,逐层训练网络,并在顶层形成分类面; 最后,用训练好的深度信念网络对人脸样本进行识别.在ORL、YALE和FERET人脸库上的实验结果表明,所提算法与采用支持向量机(SVM)的方法相比,在小样本的人脸识别中有很好的识别效果.     

Pallel parsing of tree languages for syntactic pattern recognition

Several software engineering techniques are proposed for the implementation of a more efficient Error-Correcting Tree Automata (ECTA). The production rules of a tree grammar are transformed into suitable internal codes by a lexical analyzer during the preprocessing phase, thus, several more efficient searching algorithms such as binary search, hashing techniques or table-lookup can then be used to improve the parsing efficiency. A parallel parsing algorithm of tree languages is then introduced. Comparisons of speed gain vs overhead of parallel algorithms are presented. Illustrative examples include the application of the proposed parallel algorithms to the interpretation of LANDSAT data and the discrimination of textures. Simulation results of the proposed parallel algorithm are presented.     

Automatic classification of grains via pattern recognition techniques

During production, storage and shipment, a crop of feed grain is often contaminated with admixtures of other grains or foreign material. Failure to meet the contractural limits of purity can result in monetary penalties or may prevent completion of the sales transaction. Presently, purity is established by human inspectors. They subject a carefully selected sample to 100 per cent visual inspection.This paper describes part of the development of a high speed, automatic sorting and grading procedure. A recursive learning pattern classification scheme is described which yields an overall accuracy of about 98 per cent.     

Size and shape analysis techniques for design

A major problem in designing highly specialized equipment such as oxygen masks, respirators, etc, is that the effectiveness of the equipment depends on its appropriateness for the size and shape of the body part for which it is designed. However, in general, among the individuals who are likely to be using this equipment, there is considerable heterogeneity in size and shape of the body parts. One solution is to use the available data to form homogeneous clusters of the population and then make separate designs for each cluster, commonly referred to as sizing. Current sizing practices are hindered by a problem termed 'observer-inherence'; in other words, the positioning and orientation of the reference axis system can affect the size and shape groupings more than size and shape themselves do. The impact of observer-inherence is felt most on systems that require the most stringent fit, such as helmets with optical systems. For such systems, traditional measures and analysis practices can be almost useless. In this paper, an analysis technique is introduced which should be observer-invariant in the three-dimensional case. The method is illustrated using points selected along a horizontal cross-section. The points are first transformed into values called curvatures which are subsequently transformed into a series of Fourier coefficients. These are then used for arriving at shape clusters or groupings. The shape differences (and similarities) within and between clusters are examined graphically and discussed. The technique developed here can be extended to form clusters using the curvatures of a surface instead of that of a cross-section (ie, can be extended to the three-dimensional case) and methods for doing so are discussed.     

几种模式识别方法在生物信息学中的应用

评述了几种化学模式识别方法如主成分分析、聚类分析、人工神经网络和SIMCA分类法在生物信息学中的进展,主要介绍了它们在生物信息领域中的应用。     

Analysis of pattern recognition techniques for in-air signature biometrics

As a result of advances in mobile technology, new services which benefit from the ubiquity of these devices are appearing. Some of these services require the identification of the subject since they may access private user information. In this paper, we propose to identify each user by drawing his/her handwritten signature in the air (in-air signature). In order to assess the feasibility of an in-air signature as a biometric feature, we have analysed the performance of several well-known pattern recognition techniques—Hidden Markov Models, Bayes classifiers and dynamic time warping—to cope with this problem. Each technique has been tested in the identification of the signatures of 96 individuals. Furthermore, the robustness of each method against spoofing attacks has also been analysed using six impostors who attempted to emulate every signature. The best results in both experiments have been reached by using a technique based on dynamic time warping which carries out the recognition by calculating distances to an average template extracted from several training instances. Finally, a permanence analysis has been carried out in order to assess the stability of in-air signature over time.