Structural analysis of Arabic handwriting: segmentation and recognition

In this paper, a structural method of recognising Arabic handwritten characters is proposed. The major problem in cursive text recognition is the segmentation into characters or into representative strokes. When we segment the cursive portions of words, we take into account the contextual properties of the Arabic grammar and the junction segments connecting the characters to each other along the writing line. The problem of overlapping characters is resolved with a contour-following algorithm associated with the labelling of the detected contours. In the recognition phase, the characters are gathered into ten families of candidate characters with similar shapes. Then a heterarchical analysis follows that checks the pattern via goal-directed feedback control.     

PMUTs for Handwriting Recognition

ABSTRACT

Piezoelectric micromachined ultrasonic transducers based on PZT-coated membrane structures has been fabricated, packaged and tested. A handwriting recognition system composed of three fabricated transducers is proposed. Due to its small size and low cost, this PMUTs handwriting recognition system is extraordinary promising in portable computer, cellular phone and many other minitype digital devices.     

一种手写维吾尔文字母识别算法

针对手机手写维吾尔文字母输入需求,结合手机软硬件资源局限性,提出将维吾尔文字符分成主体笔画与附属笔画两部分。采用笔画数、主体笔画结构特征、附件结构特征等21个特征为特征集,建立维吾尔文字符识别数据样本库。按笔画数粗分类,分别抽取主笔画的特征与附件的特征并用二值化数据表示,与样本库中特征数据进行异或运算,取运算后1的个数最少的样本为识别样本并给出候选样本,平均一次正确识别率达到97%。     

基于粗糙集正域的手写字母识别算法

针对手写字母识别的特点,结合粗糙集相关理论,提出了一种新的手写字母识别算法。通过对采集的样本进行正态分布假设验证,保证样本的可靠性;利用粗糙集上近似、下近似以及正域概念,对手写样本决策系统进行特征选择以简化决策系统,并进一步提炼手写分类规则。实验结果表明,新算法具有较高的识别准确率,是有效可行的。     

SEGMENTATION OF OFF-LINE CURSIVE HANDWRITING USING LINEAR PROGRAMMING

Segmentation of cursive words into letters has been one of the major problems in handwriting recognition. We introduce a new segmentation algorithm, guided in part by the global characteristics of the handwriting. We find the successive segmentation points by evaluating a cost function at each point along the baseline. The cost of segmenting at a point is a weighted sum of four feature values at that point. The weights of the features are determined using linear programming.In our tests with 750 words written by 10 writers, 97% of the letter boundaries were correctly located.     

基于手写体的身份识别

以前许多文章曾介绍过一些基于手写体的书写人身份识别技术，其中多数都假设所写的文本是固定的。本文中，我们试图通过一种自动的不依赖文本的书写人识别听新颖算法，来消除这种假设，假定不同的人手写体存在明显的区别，我们采用一种综合方法，它基于纹理分析，每个人的手写体都被看成一种不同的纹理。原则上，我们可以采用任意一种标准的纹理识别算法（例如：多通道伽柏滤波器方法）。在对40名书写人的1000份测试文档的分类中，测试结果非常令人满意，识别率最高达到了96%。     

基于混沌序列的SVM参数选择及其在笔迹鉴别中的应用

基于RBF核的支持向量机(SVM)模型选择取决于两个参数，即惩罚因子和核参数，为了寻找SVM参数的最优组合，利于笔迹鉴别图像的自动识别，提出了基于混沌序列的参数搜索算法以实现SVM模型参数的自动选择。从与网格法和双线性法进行的比较实验可以看出，基于混沌序列的SVM参数选取更简单，更易于实现，并使SVM具有更好的推广能力。在10人笔迹灰度图像库上分类识别实验结果表明，该方法不但可以提高分类识别率，而且显著减少了训练SVM的个数。     

Multifactor authentication as a protection mechanism in computer networks

A direction of authentification is considered that is a component of the problem of creating mechanisms for information protection in computing systems (CS). The proposed mechanism of multifactor authentication makes it possible to increase the degree of security of authentication procedures in CS, which is especially important in practice. Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 170–175, September–October, 1999.     

Arabic Word Recognition by Classifiers and Context

Given the number and variety of methods used for handwriting recognition, it has been shown that there is no single method that can be called the "best". In recent years, the combination of different classifiers and the use of contextual information have become major areas of interest in improving recognition results. This paper addresses a case study on the combination of multiple classifiers and the integration of syntactic level information for the recognition of handwritten Arabic literal amounts. To the best of our knowledge, this is the first time either of these methods has been applied to Arabic word recognition. Using three individual classifiers with high level global features, we performed word recognition experiments. A parallel combination method was tested for all possible configuration cases of the three chosen classifiers. A syntactic analyzer makes a final decision on the candidate words generated by the best configuration scheme. The effectiveness of contextual knowledge integration in our application is confirmed by the obtained results.     

基于云计算平台的手写识别系统

本文利用Enomaly虚拟云架构技术设计了一个云手写识别系统,除了提供高准确率的识别功能外,同时使得倾斜书写识别、用户自适应识别等需要高计算及存储资源的功能实现成为可能。实验结果表明,传统C/S模式的传统服务器在用户并发数为300时处理能力已经达到极限,而采用基于云计算架构的手写识别系统能轻松处理1000个并发用户的服务请求,在处理300个并发用户时,接入率为100%,远高于传统服务器模式的接入率(82.7%),平均识别处理时间仅为16ms,大大低于传统服务器模式的处理时间(340ms)。