基于人脸识别的远程身份验证系统

文章介绍了一种基于人脸识别的C/S结构的远程身份验证系统,讨论了系统结构与关键技术,给出了实验结果.系统采用奇异值分解和判别式KL投影提取特征,利用最邻近法进行分类,适用于人脸样本数量不是很大的情况.实验证明系统达到了较好的应用效果.     

基于神经网络和学习子空间的OCR识别方法在选票处理中的应用

选票信息的自动处理能提高录入速度、保证选的公正性，绝大多数的选票信息自动处理系统都是采用光学标记识别的方法。该方法对于选票纸张和填写要求较高，而且误识率较高，该文提出了一种基于神经网络和学习子空间光学字符识别（OCR）方法。该识别方法具有对纸张和填写的要求低，精度高、通用性好的特点。     

人耳识别技术研究进展综述

人耳识别是一种新的生物特征识别技术,目前,研究尚处于起步阶段,有关的理论和方法还很不完善。文章首先介绍了人耳自动系统的构成,然后分析了现有的各种人耳识别技术,最后提出了展望。     

Learning to Perceive Objects for Autonomous Navigation

Current machine perception techniques that typically use segmentation followed by object recognition lack the required robustness to cope with the large variety of situations encountered in real-world navigation. Many existing techniques are brittle in the sense that even minor changes in the expected task environment (e.g., different lighting conditions, geometrical distortion, etc.) can severely degrade the performance of the system or even make it fail completely. In this paper we present a system that achieves robust performance by using local reinforcement learning to induce a highly adaptive mapping from input images to segmentation strategies for successful recognition. This is accomplished by using the confidence level of model matching as reinforcement to drive learning. Local reinforcement learning gives rises to better improvement in recognition performance. The system is verified through experiments on a large set of real images of traffic signs.     

基于视频识别的虚拟踩气球系统

介绍了利用视频识别技术实现虚拟踩气球的一个人机交互系统的实现过程及其关键技术．根据光照原理和彩色感知数学模型推导出了光照强度校正法，并结合色调匹配的原理提出了一个光照色调颜色校正算法，并通过试验验证了其算法的合理性。     

Time scale modification and vocal tract length normalization for improving the performance of Tamil speech recognition system implemented using language independent segmentation algorithm

This paper describes the work done in improving the performance of Tamil speech recognition system by using Time Scale Modification (TSM) and Vocal Tract Length Normalization (VTLN) techniques. The speech recognition system for Tamil language was developed using a new approach of text independent speech segmentation, with a phoneme based language model for recognition. There is degradation in the performance of speech recognition due to variations in the speaking rate and vocal tract shape among different speakers. In order to improve the performance of speech recognition system, both TSM and VTLN normalization techniques were used in this work. The TSM was implemented using the Phase vocoder approach and the VTLN was implemented using speaker specific bark/mel scale in bark/mel domain. The performance of Tamil speech recognition system was improved by performing both TSM and VTLN normalization techniques.     

Hybrid evolutionary learning for synthesizing multi-class pattern recognition systems

This paper describes one aspect of a machine-learning system called HELPR that blends the best aspects of different evolutionary techniques to bootstrap-up a complete recognition system from primitive input data. HELPR uses a multi-faceted representation consisting of a growing sequence of non-linear mathematical expressions. Individual features are represented as tree structures and manipulated using the techniques of genetic programming. Sets of features are represented as list structures that are manipulated using genetic algorithms and evolutionary programming. Complete recognition systems are formed in this version of HELPR by attaching the evolved features to multiple perceptron discriminators. Experiments on datasets from the University of California at Irvine (UCI) machine-learning repository show that HELPR’s performance meets or exceeds accuracies previously published.     

多技术合力的人脸识别系统设计

人脸识别系统结构复杂,也包含了多种技术.从多个角度阐述了多技术合力的人脸识别系统设计方法,内容涉及人脸图像采集、人脸识别算法、并行处理、综合系统集成4个部分.多技术合力的人脸识别系统设计方法体现了速度与智能化相结合的优势,也体现了系统的完备性和性能的互补性.给出了该方法在人脸识别率和识别速度上达到的性能指标,并给出了所设计的人脸识别系统的部分突出应用.     

指纹识别系统的设计与实现

本文研究了嵌入式指纹识别系统的设计方法与实现技术。通过构造以ADIADSP-BF533DSP为平台的硬件环境,实现了指纹识别的嵌入式系统设计,并且针对指纹识别算法对系统运行速度的影响进行了研究,给出了实验结果,证实了该方法能够较好的构造嵌入式指纹识别系统。     

Speech Enhancement and Recognition in Meetings With an Audio–Visual Sensor Array

This paper addresses the problem of distant speech acquisition in multiparty meetings, using multiple microphones and cameras. Microphone array beamforming techniques present a potential alternative to close-talking microphones by providing speech enhancement through spatial filtering. Beamforming techniques, however, rely on knowledge of the speaker location. In this paper, we present an integrated approach, in which an audio-visual multiperson tracker is used to track active speakers with high accuracy. Speech enhancement is then achieved using microphone array beamforming followed by a novel postfiltering stage. Finally, speech recognition is performed to evaluate the quality of the enhanced speech signal. The approach is evaluated on data recorded in a real meeting room for stationary speaker, moving speaker, and overlapping speech scenarios. The results show that the speech enhancement and recognition performance achieved using our approach are significantly better than a single table-top microphone and are comparable to a lapel microphone for some of the scenarios. The results also indicate that the audio-visual-based system performs significantly better than audio-only system, both in terms of enhancement and recognition. This reveals that the accurate speaker tracking provided by the audio-visual sensor array proved beneficial to improve the recognition performance in a microphone array-based speech recognition system.     

鲁棒的多体印刷英文识别系统的实现

文章讨论了设计一个实用的多体英文识别系统中解决的主要问题。该系统能识别多达260种字体,包括斜体和黑体等字体,对训练集的识别率达到99%,对实际文本测试的错误率比TH-OCR2000低56%。文章详细阐述了文本行字切分,特征提取和分类器设计,以及后处理所使用的常用技术,对各种技术的特点进行了分析和比较,并提出了一些新的技术。文章对于OCR系统的设计具有一定的指导意义。     

Knowledge acquisition techniques for feature recognition in CAD models

Automatic Feature Recognition (AFR) techniques are an important tool for achieving a true integration of design and manufacturing stages during the product development. In particular, AFR systems offer capabilities for recognising high-level geometrical entities, features, in Computer-Aided Design (CAD) models. However, the recognition performances of most of the existing AFR systems are limited to the requirements of specific applications. This paper presents automatic knowledge acquisition techniques to support the development of AFR systems that could be deployed in different application domains. In particular, a method to generate automatically feature recognition rules is proposed. These rules are formed by applying an inductive learning algorithm on training data consisting of feature examples. In addition, a technique for defining automatically feature hints from such rule sets is described. The knowledge acquisition techniques presented in this study are implemented within a prototype feature recognition system and its capabilities are verified on two benchmarking parts.     

Segment-based emotion recognition from continuous Mandarin Chinese speech

Recognition of emotion in speech has recently matured to one of the key disciplines in speech analysis serving next generation human-machine interaction and communication. However, compared to automatic speech recognition, that emotion recognition from an isolated word or a phrase is inappropriate for conversation. Because a complete emotional expression may stride across several sentences, and may fetch-up on any word in dialogue. In this paper, we present a segment-based emotion recognition approach to continuous Mandarin Chinese speech. In this proposed approach, the unit for recognition is not a phrase or a sentence but an emotional expression in dialogue. To that end, the following procedures are presented: First, we evaluate the performance of several classifiers in short sentence speech emotion recognition architectures. The results of the experiments show that the WD-KNN classifier achieves the best accuracy for the 5-class emotion recognition what among the five classification techniques. We then implemented a continuous Mandarin Chinese speech emotion recognition system with an emotion radar chart which is based on WD-KNN; this system can represent the intensity of each emotion component in speech. This proposed approach shows how emotions can be recognized by speech signals, and in turn how emotional states can be visualized.     

A corpus for OCR research on mathematical expressions

This paper is concerned with research on OCR (optical character recognition) of printed mathematical expressions. Construction of a representative corpus of technical and scientific documents containing expressions is discussed. A statistical investigation of the corpus is presented, and usefulness of this analysis is demonstrated in the related research problems, namely, (i) identification and segmentation of expression zones from the rest of the document, (ii) recognition of expression symbols, (iii) interpretation of expression structures, and (iv) performance evaluation of a mathematical expression recognition system. Moreover, a groundtruthing format has been proposed to facilitate automatic evaluation of expression recognition techniques. Received: 10 July 2003, Accepted: 22 November 2004, Published online: 18 March 2005 Correspondence to: Utpal Garain     

车载警示系统的设计与研究

针对当前电子摄像与曝光系统的实时性差,警示性不足的特点,本文设计了一种车载警示系统,该系统是基于数字电子摄像、图像处理、模式识别和电子曝光等技术原理,增加了无线发射与接收的装置,采取特征矢量字符识别技术和信息的并发操作处理技术,设计的一种创新的在交通违规的第一时间现场实时发出警示信息的智能识别系统。