Gesture Recognition Summarization

Gesture recognition is an important research in the field of human-computer interaction. Hand Gestures are strong variable and flexible, so the gesture recognition has always been an important challenge for the researchers. In this paper, we first outlined the development of gestures recognition, and different classification of gestures based on different purposes. Then we respectively introduced common methods used in the process of gesture segmentation, feature extraction and recognition. Finally, the gesture recognition was summarized and the studying prospects were given.     

Gender Recognition by MULBP

Gender recognition has gained more attention. However, most of the studies have focused on face images acquired under controlled conditions. In this paper, we investigate gender recognition on real-life faces. We proposed a gender recognition scheme, which is composed of four parts: face detection, median filter, feature extraction, and gender classifier. MULBP features are adopted and combined with a SVM classifier for gender recognition. The MULBP feature is robust to noise and illumination variations. In the experiment, we obtain 98.32% using LFW database and 97.30% on Samsung Gender dataset, which shows the superior performance in gender recognition compared with the conventional operators.     

Online face recognition system based on multi-view algorithm and Kernel PCA

An online face recognition system is presented in the paper. To online face recognition system, we should consider the recognition rate, the image compression and image size. In the paper we researched the innovation technologies for face recognition system, including Kernel Principal Component Analysis （Kernel PCA）, Delta low-pass wavelet filter, and face recognition algorithm using multiple images. Kernel PCA is derived to classify the characteristics of training images in the database. Delta low-pass wavelet filter is used to reduce the image size. A face recognition algorithm using multiple images is presented to improve the recognition rate. Simulation experiment shows that in the case of packet loss recognition rate is improved highly.     

Application of SVM in Feather and Down Category Recognition

Currently, feather and down category recognition is often done by man with a microscope, but this method has some disadvantages. Applying SVM （Support Vector Machine） to feather and down category recognition is proposed in this paper, feather and down category recognition is done by computer automatically. After image processing, the triangle nodes of two-value image of feather are to be recognized with SVM, then the triangle nodes which have been recognized will be matched and the distance between the matched triangle nodes is calculated. In the end, the feather and down category is recognized. In order to improve recognition rate, we retrain it when training SVM.     

Application of Support Vector Machine in Weld Defect Detection and Recognition of X-ray Images

Support vector machines（SVM） received wide attention for its excellent ability to learn, it has been applied in many fields. A review of the application of SVM in weld defect detection and recognition of X-ray image is been presented. We will show some commonly used methods of weld defect detection and recognition using SVM, and the advantages and disadvantages of each method will be discussed. SVM appears to be promising in weld defect detection and recognition, but future research is needed before it fully mature in this filed.     

De-noising with Novel DWT-MFCC for Speaker Recognition

In this paper, three modifications for speaker recognition are presented. First, for threshold in the wavelet domain, a semi-soft threshold function that shows advantages over hard and soft threshold function with respect to variance and bias of the estimated value is used. Second, in the classical cepstrum calculation, a log transtbrmation is used to modify the power spectrum, Generally this transformation is done after the filter-bank. This paper shows that performing this transformation before the filter bank is more interesting in the experiment. The experiment shows that the proposed method has more advantages for speaker recognition in noise circumstance than the speaker recognition with simple MFCC （Mel-scale Frequency Cepstral Coefficients）. Third, in order to improve recognition performance and training velocity, modified OGMM is applied in recognition stage. The proposed method has very good guidance for real-time speaker recognition.     

On spam detection based on cognitive pattern recognition

A method of spam detection, based on cognitive pattern recognition, had been proposed. The connection between Email category and cognition of Email user interest within life and work, had been analyzed. Under the guidance of cognitive pattern recognition theory, the mechanism of spam detection, based on intelligent cognition of Email user interest within life and work, had been discussed. Then the spam detection algorithm and its concrete implementation was given. Experimental results demonstrate that the spare detection algorithm has a good learning ability, scalability, and a good ability to achieve high recognition accuracyn     

Research and Implementation for License Plate Recognition Based on Improved Projection Algorithm简

This paper analyzes and dissertates the discrete wavelet transform and improved projection algorithm in four kernel stages （image preprocessing, license plate localization, character segmentation, license plate recognition, i.e.） of license plate recognition system in detail. At last, it gives some conclusions and suggestions on future research.     

A vehicle re-identification algorithm based on multi-sensor correlation

Magnetic sensors can be applied in vehicle recognition. Most of the existing vehicle recognition algorithms use one sensor node to measure a vehicle’s signature. However, vehicle speed variation and environmental disturbances usually cause errors during such a process. In this paper we propose a method using multiple sensor nodes to accomplish vehicle recognition. Based on the matching result of one vehicle’s signature obtained by different nodes, this method determines vehicle status and corrects signature segmentation. The co-relationship between signatures is also obtained, and the time offset is corrected by such a co-relationship. The corrected signatures are fused via maximum likelihood estimation, so as to obtain more accurate vehicle signatures. Examples show that the proposed algorithm can provide input parameters with higher accuracy. It improves the av-erage accuracy of vehicle recognition from 94.0%to 96.1%, and especially the bus recognition accuracy from 77.6%to 92.8%.     

An Automatic Digital Camera Based Fingerprint Verification System

The emergence of touch-less fingerprint recognition system brings both advantages and challenges in the automated fingerprint recognition research. In this paper, we proposed a touch-less fingerprint recognition system by using a digital camera. The system frees from the problems in term of deformation caused by the contact pressure, hygienic, maintenance and latent fingerprints that exist in the touch-based fingerprint recognition system. However, fingerprint images that were acquired with digital camera consist of low ridge-valley contrast, defocus and motion blurriness problems. Hence, preprocessing steps are introduced to reduce those problems. The system comprises of preprocessing, Gabor filter feature extraction, Principle Component Analysis and verification using Support Vector Machine. Satisfactory results are attained in our acquired fingerprint database.     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

法律信息库系统

本文分析了法律数据库的结构和特点，介绍了采用面向对象设计方法和超文本数据库技术开发和实现法律信息库系统将作为重要网络资源之一为不同用户进行法律咨询服务。     

International Journal of Automation and Computing Table of Contents

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Information for authors

正SCIENCE CHINA Information Sciences(Sci China Inf Sci),cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China,and published by Science China Press,is committed to publishing highquality,original results of both basic and applied research in all areas of information sciences,including computer science and technology;systems science,control science and engineering(published in Issues with odd numbers);information and communication engineering;electronic science and technology(published in Issues with even numbers).Sci China Inf Sci is published monthly in both print and electronic forms.It is indexed by Academic OneFile,Astrophysics Data System(ADS),CSA,Cabells,Current Contents/Engineering,Computing and Technology,DBLP,Digital Mathematics Registry,Earthquake Engineering Abstracts,Engineering Index,Engineered Materials Abstracts,Gale,Google,INSPEC,Journal Citation Reports/Science Edition,Mathematical Reviews,OCLC,ProQuest,SCOPUS,Science Citation Index Expanded,Summon by Serial Solutions,VINITI,Zentralblatt MATH.     

Erratum to: Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal

正Erratum to:J Zhejiang Univ-Sci C(ComputElectron)2014 15(7):551-563doi:10.1631/jzus.C1300320The original version of this article unfortunately contained mistakes.Algorithm 6 should be as follows:Algorithm 6 FGKFCM-F clustering Input:(1)X={x_1,x_2,…,x_N},,x_iR~d,i=1,2,…,N,the dataset;(2)C,1C≤N,the number of clusters;(3)ε0,the stopping criterion;     

Journal of Zhejiang University-SCIENCE C (Computers & Electronics) Total contents

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磨机负荷专家控制系统设计及仿真研究

磨矿过程的大滞后和时变性等特点,致使对磨机负荷的最佳工作点很难进行稳定、高效的控制,针对以上情况,借鉴生物界的免疫反馈原理和遗传算法,利用模糊控制可以有效地实现对非线性、纯滞后、复杂的对象进行控制的优点,并结合PID与自寻优方法,设计出磨机负荷专家控制系统,用VB编写OPC客户端及控制程序,实现对磨机负荷的动态优化控制;试验结果表明,文章提出的控制策略能够增强系统的稳定性,且在干扰存在的情况下也能很好的跟随系统的参数变化,在提高磨机台时产量的同时增加了矿厂的经济效益.     

基于人工蜂群的无线传感器网络能耗均衡算法

由于无线传感器网络中的节点链路状况、数据传输能耗及节点剩余能量的限制,造成网络中部分感知节点寿命缩短,影响网络生存周期,提出了一种基于人工蜂群算法的WSNs能耗均衡算法,优化网络能耗均衡,从而提高网络寿命;文章给出了网络能耗相应的数学模型及优化求解算法,介绍人工蜂群算法的寻找食物过程,阐述了人工蜂群算法在网络能耗均衡方面的实现步骤;通过实验仿真证明,文章提到的算法与LEACH分簇算法、蚁群优化算法相比,具有更好的能耗和负载均衡能量、丢包率和时延性,有效地提高了网络生存周期.