An FPGA-based face recognition using combined 5/3 DWT with PCA methods

This paper describes a new scheme for feature extraction from facial images on FPGA. The proposed method is comprised of two stages. The first stage uses the 5/3 DWT to decompose the original face image into LL, LH, HL, and HH wavelet coefficient to reduce the size of the image. In the second stage, PCA is employed to extract the face features from the wavelet coefficients. Here we use the power iteration algorithm to find the eigenvector of the covariance matrix. We present an efficient hardware architecture using combination of parallel processing module and serial processing module. This method can take the benefits of parallel usage advantage of FPGAs and can save hardware resources. Complete hardware implemented on a Stratix II FPGA. The experimental results show that the system works with high processing rate and only 21% of the logic resources an FPGA are consumed by face recognition logic Thus it is very suitable for the low cost implementation of the face recognition system.     

A new ensemble feature selection and its application to pattern classification

Neural network ensemble based on rough sets reduct is proposed to decrease the computational complexity of conventional ensemble feature selection algorithm. First, a dynamic reduction technology combining genetic algorithm with resampling method is adopted to obtain reducts with good generalization ability. Second, Multiple BP neural networks based on different reducts are built as base classifiers. According to the idea of selective ensemble, the neural network ensemble with best generalization ability can be found by search strategies. Finally, classification based on neural network ensemble is implemented by combining the predictions of component networks with voting. The method has been verified in the experiment of remote sensing image and five UCI datasets classification. Compared with conventional ensemble feature selection algorithms, it costs less time and lower computing complexity, and the classification accuracy is satisfactory.     

用现代设计包装传统民间艺术精粹——潍坊年画的包装设计研究

潍坊年画具有浓郁的乡土气息和淳朴鲜明的艺术风格,在包装设计中应通过分析潍坊年画的精神内涵和吉祥寓意,通过对色彩、图形、文字等表象性要素的设计探索,抓住年画文化的本质和精神核心,把它融入到具体设计中,将年画传统的文化思想精髓同当代设计要素有机结合起来,创造具有鲜明艺术个性的包装设计形式。     

一种基于多Agent的分布式入侵检测系统设计

在分析现有基于Agent的入侵检测系统的基础上,提出了一种基于多Agent分布式入侵检测系统模型。该模型采用了分布检测、分布响应的模式,各Agent之间具有良好的相对独立性。通过多Agent技术的思想建立系统总体结构,给出了模型的各个组成部分,并对结构中各种Agent与中心控制台的功能设计进行了分析。同时对涉及到特征匹配算法、动态选举算法、协同算法进行了初步的设计与分析。系统可充分利用各Agent的协同完成入侵检测任务,实时响应,可有效地改进传统IDS。     

基于DHT的P2P资源定位的研究

文章对DHT的P2P资源定位进行了分析和比较,并对Chord模型进行了改进。提出了一个新的模型TL—Chord。该模型将自治域中的超级节点上的缓存表的资源定位机制与Chord的资源定位相结合,缩短了搜索路径长度,缩小了路由时间。     

Numeric and curve parameters for freeform surface feature models

The success of feature modelling systems depends to a large extent on offering user-friendly ways for specifying and varying feature models. In this paper, several new facilities are introduced for this.Numeric and curve parameters are presented for specification and variation of freeform surface feature models. Several properties of the parameters can be defined, such as the direction of evaluation for a curve parameter. In addition to parameters present in features, other parameters can be added to a feature model, including intersection curves between features.To provide these facilities, a new three-level structure is introduced, which includes a partially evaluated model that can capture new generic model entities, including feature intersection curves. The work has been implemented in a prototype surface feature modelling system with functionality for feature class definition, feature model creation, and advanced feature model variation through the new types of parameters.     

基于曲率流的点模型编辑方法*

为了对点模型表面进行保细节的自由形状编辑,提出了一种基于曲率流的点模型形状编辑方法。该方法定义了基于平均曲率流的光顺算子,通过此光顺算子获得点模型不同光滑程度的曲面表示。运用对应曲面上点之间的向量差进行相应几何细节的抽取,在相邻的曲面表示之间将几何细节剥离出来。用户可以在不同的曲面上进行自由形状编辑,而无须关心几何细节。在变形后的曲面上再将相应的几何细节映射回去,实现对模型保细节的变形。实验结果表明该方法是一种有效的点模型造型算法,在变形的同时,有效地保持了模型表面的细节特征。     

基于小波过零点检测的虹膜识别方法研究*

在经典过零点算法的基础上,改进特征提取与匹配算法。分析各阶高通小波系数在同一算法下的识别率,以此选择小波系数来综合编码分析。采用不同的小波滤波器进行分析,考察不同的小波滤波器对算法的影响。DB3小波的识别率为99.61%,等错率为0.41%;四次B样条小波识别率为99.75%,等错率为0.25%;Coif3小波识别率为99.72%,等错率为0.29%。第五、六阶小波高通系数涵盖了虹膜纹理的主要信息,可采用第五、六阶小波系数进行编码识别。不同的小波滤波器得到的结果区别不是很大,DB3、四次B样条、Coif3     

特征权对贝叶斯分类器文本分类性能的影响

在文本分类研究中,人们希望用特征权来改善文本分类效果。以最优分类器——贝叶斯分类器为基准分类器,研究了特征权对文本分类性能的可能影响。理论推导表明,就最优分类器而言,特征权不能有效提高文本分类效果。     

基于支持向量机的纸张缺陷图像分类识别

根据支持向量机（SVM）在小样本、高维模式分类中具有的优良分类性能,提出将支持向量机应用于实际的纸张缺陷分类。针对三种现场易出现的缺陷,通过对缺陷图像进行预处理、特征选择,再利用SVM进行分类,利用交叉验证进行参数和模型选取,取得了较好的分类效果,为纸张缺陷的分类指出一种可行的方法。