快速道路标志辅助识别系统

本文提出了对道路标志进行快速别的一种辅助系统,该系统以人类的视觉及思维模式作为蓝本,可以较为快速的实现行进汽车中的交通标志识别。这一系统通过安装在汽车上的摄像机获取信息,通过子采样消除图像重影同时减少需要处理的数据量,然后根据交通标志的色彩和形状两方面特征,寻找画面帧中的交通标志,采用模板匹配的方法实现标志的定位和最终识别。     

Shape-based word recognition

We describe a process of word recognition that has high tolerance for poor image quality, tunability to the lexical content of the documents to which it is applied, and high speed of operation. This process relies on the transformation of text images into character shape codes, and on special lexica that contain information on the shape of words. We rely on the structure of English and the high efficiency of mapping between shape codes and the characters in the words. Remaining ambiguity is reduced by template matching using exemplars derived from surrounding text, taking advantage of the local consistency of font, face and size as well as image quality. This paper describes the effects of lexical content, structure and processing on the performance of a word recognition engine. Word recognition performance is shown to be enhanced by the application of an appropriate lexicon. Recognition speed is shown to be essentially independent of the details of lexical content provided the intersection of the occurrences of words in the document and the lexicon is high. Word recognition accuracy is dependent on both intersection and specificity of the lexicon. Received May 1, 1998 / Revised October 20, 1998     

基于依存分析的事件识别

事件抽取是信息抽取的重要组成部分,事件识别是事件抽取的基础,事件识别的效果直接影响了事件抽取的结果.基于机器学习的方法识别事件需要从词汇中发掘更多的特征.针对当前事件识别方法中存在的不足,提出了一种基于依存分析的事件识别方法.用依存分析发掘触发词与其它词之间的句法关系,以此为特征在SVM分类器上对事件进行分类,最终实现事件识别.实验表明,基于依存分析的事件识别优于传统的事件识别方法,而融合多特征的事件识别F值可提高到69.3%.     

Evaluation of word spotting under improper segmentation scenario

International Journal on Document Analysis and Recognition (IJDAR) - Word spotting is an important recognition task in large-scale retrieval of document collections. In most of the cases, methods...     

关联规则在汉语词属性中的研究

在语音识别和合成中文本分析是很重要的,文本分词是文本分析正确与否的基础。目前语音合成系统中的分词一般是基于词典分析建立的,对于多音字易产生错误。文章基于数据挖掘中的关联规则的发现方法对文本分词中词语的关联关系进行研究,通过文本数据的文本特征及语音特征描述的有机结合,获取词语自身属性的关联关系,最后进行了实例测评。     

在MATLAB环境下实现的语音识别

介绍了一种基于MATLAB的多个特定人连接词语音识别的方法，并提出了在进行端点检测时，引入平均的概念能进一步提高识别率。此设计是以LPCC系数、DTW算法为核心的基于图形界面的设计。通过大量的实验测试，表明该方法基本达到屏蔽外界环境的影响，具有非常高的精度识别。     

基于DSP的人脸图像识别系统

本文介绍了便携式的人脸辨识系统，采用DSP控制，电路简单，可靠性高，应用灵活，是人脸模式识别新的发展途径之一。     

扑克牌识别软件包的开发及应用

该文介绍了基于模式识别原理开发的扑克牌识别软件包及其程序实现，在识别中运用了BP神经网络和相关检测两种方法，取得了较好的识别效果，最后通过两个具体扑克牌的识别dermo简单给出了该扑克牌识别软件包的应用。     

中文篇章级句间语义关系识别

篇章句间关系识别(Discourse Relation Recognition)是篇章分析的重要内容,该文对中文篇章句间关系识别任务进行初步探索,包括显式篇章句间关系识别与隐式篇章句间关系识别两类任务。针对显式篇章句间关系,我们提出基于关联词规则的方法进行识别,取得了很好的效果;针对隐式篇章句间关系,我们抽取词汇、句法、语义等特征,采用有指导模型进行识别。该文的分析和实验结果为后续研究提供了参考和基本对照系统。     

基于数字图像处理的车牌定位方法的研究

车牌识别是现代智能交通系统中的重要组成部分之一,其应用范围十分广泛。对车牌定位方法进行了初步研究,以模式识别、数字图像处理、计算机视觉技术为基础,使用M atlab软件对图像预处理、边缘检测等算法进行了必要的仿真实验,获取了车牌区域。对摄像机拍摄车辆的图像进行分析处理可以得到汽车的车牌号码,从而完成整个识别过程。     

多文种环境下汉字内码识别算法的研究

汉字内码向ISO/IEC 10646过渡是实现计算机用文字编码统一的必然趋势,但目前在一段时间内仍将存在多种汉字内码并存的情况,所以实现汉字内码的自动识别是保证汉字多内码并存的关键。本文主要探讨了如何在多内码并存的多文种环境中实现汉字内码自动识别的问题,并提供了多种汉字内码识别算法,包括基于内码分布、标点符号特征、字频特征和语义特征的识别算法等。在此基础上,本文对不同的识别算法进行分析和评估。在对目标样本的测试中,以上算法的识别率最高可以达到99.9%以上。     

More than twenty years of advancements on Frontiers in handwriting recognition

In this paper the results of the research in handwriting/handwritten character recognition in about the last quarter of a century are reported, illustrating the results presented during the International Workshop on Frontiers in Handwriting Recognition (IWFHR) and the International Conference on Frontiers in Handwriting Recognition (ICFHR).     

Efficient MLP constructive training algorithm using a neuron recruiting approach for isolated word recognition system

This paper describes an efficient constructive training algorithm using a Multi Layer Perceptron (MLP) neural network dedicated for Isolated Word Recognition (IWR) systems. Incremental training procedure was employed and this approach was based on novel hidden neurons recruiting for a single hidden-layer. During Neural Network (NN) training phase, the number of pronunciation samples extracted from the Training Data (TD) was sequentially increased. Optimal structure of the NN classifier with optimized TD size was obtained using this proposed MLP constructive training algorithm.     

A review on Gabor wavelets for face recognition

Due to the robustness of Gabor features against local distortions caused by variance of illumination, expression and pose, they have been successfully applied for face recognition. The Facial Recognition Technology (FERET) evaluation and the recent Face Verification Competition (FVC2004) have seen the top performance of Gabor feature based methods. This paper aims to give a detailed survey of state of the art 2D face recognition algorithms using Gabor wavelets for feature extraction. Existing problems are covered and possible solutions are suggested.     

基于单张二维照片的三维姿态计算

通过一张二维照片计算其三维姿态是三维人脸识别和颅像重合中的难点问题。该文主要研究了绕轴的平面旋转、垂直深度旋转和侧深度旋转的姿态计算问题。通过两外眼点间的关系计算平面旋转角度；通过眉间点、鼻下点与颏下点的距离关系计算垂直深度旋转角度；通过鼻下点与两外眼点的角度关系计算侧深度旋转角度。试验证明提出的方法误差小，能够比较准确地计算出三维姿态。     

基于语义角色标注的新闻领域复述句识别方法

复述(Paraphrase)句的识别可看作文本蕴含(Text Entailment)识别的一个子问题,传统的解决方法是通过词频或句法上的相似度来判断。即使用相同的文字书写的句子其含义也可能差别很大,而相同句法结构也不能保证意义一致。该文根据新闻语料的特点,提出了一种通过引入深层的语义角色标注来帮助识别新闻领域复述句的方法。该方法通过在语义角色这种结构化的含义表达形式中提取的特征来弥补传统方法的不足 先识别待判断的两个句子中所有谓词的语义角色,然后计算两个句子间对应语义角色的相似度,最后结合传统的句子相似度计算方法来进行相似性计算。实验证明,该文提出的方法能有效地提高复述语句的识别效果。     

机器视觉测量系统在工业在线检测中的应用

机器视觉测量用视觉传感器采集目标图像,通过对图像各种特征量的分析处理,获取被测曲面信息.设计了一机器视觉测量系统,识别一幅图像中是否存在确定大小和形状子图像,若有则识别出它的位置.介绍如何利用“模板匹配”法对目标图像进行识别,并举例如何利用系统检测药片的包装是否合格（有无漏装）.     

Maximum A Posteriori Linear Regression for language recognition

This paper proposes the use of Maximum A Posteriori Linear Regression (MAPLR) transforms as feature for language recognition. Rather than estimating the transforms using maximum likelihood linear regression (MLLR), MAPLR inserts the priori information of the transforms in the estimation process using maximum a posteriori (MAP) as the estimation criterion to drive the transforms. By multi MAPLR adaptation each language spoken utterance is convert to one discriminative transform supervector consist of one target language transform vector and other non-target transform vectors. SVM classifiers are employed to model the discriminative MAPLR transform supervector. This system can achieve performance comparable to that obtained with state-of-the-art approaches and better than MLLR. Experiment results on 2007 NIST Language Recognition Evaluation (LRE) databases show that relative decline in EER of 4% and on mincost of 9% are obtained after the language recognition system using MAPLR instead of MLLR in 30-s tasks, and further improvement is gained combining with state-of-the-art systems. It leads to gains of 6% on EER and 11% on minDCF comparing with the performance of the only combination of the MMI system and the GMM-SVM system.