Computational Analysis of Handwriting, Character Recognition, and Design of Digital Fonts

***在过去的几十年里，我们探索和开发了许多计算****技术来识别不同类型的模式，包括但不限于不同语言的手写体，以及多个****年龄段的人脸。该发现资助申请涉及以下新技术：***发现新的基于知识的*特征、降低错误率的方法***和优化不同识别算法的组合，以及***用英语、法语、阿拉伯语和***其他语言编写的字符和单词的识别。它的目的是通过结合过去几年我们在测速镜和眼动追踪实验中发现的新功能，改进我们的识别算法***，使用多级多个分类器。它将*集中于扩展我在以下***新领域的研究，并与笔迹学和心理学专家****以及字体设计师进行咨询：*****-提取更详细的独特笔迹特征，例如***形状、字符形成方式以及个人书写的特点***，以验证***笔迹与个性特征之间的*相关性，这是笔迹学中*一个具有挑战性和***争议性的话题，*并检测***作者的健康状况，例如患有帕金森病和阿尔茨海默病的人。我们相信***我们在手写识别方面的丰富经验将使我们能够为这一主题带来新的***见解，并帮助笔迹学家节省***时间来分析个人的笔迹。******-应用我们的字符识别和感知技术来评估****汽车车牌中使用的字体的易读性，并****提出新的字体设计，以通过图像处理和模式识别技术促进车牌的识别****，以帮助***执法机构找到被盗的汽车、交通犯罪行为，***不同天气条件下的车辆识别以及无人驾驶车辆的指挥***。********-扩展我们的特征提取技术，例如提取硬币上铸造的或印在纸币上的字符的关键点***，以检测***假币和纸币，这已成为影响全世界所有国家*经济的***重要课题。********-对大量数据进行密集实验，以发现帮助社会和经济发展的新***方法。我们社会的福祉。********

***Over the past decades, we have explored and developed numerous computational****techniques of recognizing different types of patterns, including but not****limited to handwriting in different languages, and human faces of multiple****age groups. This Discovery grant application is related to novel techniques of***discovering new knowledge-based*features, methods of reducing the error rate ***and optimizing the combination of different recognition algorithms, and ***the recognition of characters and words written in English, French, Arabic, and ***other languages. It is aimed at improving our recognition algorithms***using multi-stage multiple classifiers by incorporating the new features ***discovered in our tachistoscope and eye-tracking experiments during the***past years. It will be*focused on an extension of my research in the*following ***new areas in*consultation with experts in graphology and psychology,****and font designers:*******- Extract more detailed distinctive handwriting features, such as the***shapes of characters, the way characters are formed, and peculiarities***of the writing of the individuals, to validate the*correlation between ***handwriting and personality characteristics, which is*a challenging and ***controversial topic in graphology,*and to detect the health conditions of ***the writers, e.g. those with Parkinson and Alzheimer diseases. We believe***our rich experience in handwriting recognition will enable us to bring new***insights to this subject and offer help to graphologists in saving their***time to analyze the handwriting of individuals.******- Apply our character recognition and perceptive techniques to assess****the legibility of the fonts used in the license plates of automobiles and****propose new designs of fonts to facilitate the recognition of the license****plates by image processing and pattern recognition techniques to help***law-enforcement organizations in finding stolen cars, traffic offences,***identification vehicles under different weather conditions and the command***of driverless vehicles.******- Extend our feature extraction techniques, such as the extraction of keypoints***of the characters minted on the coins or printed on banknotes, to detect***fake coins and paper*money, which has become an imminent subject of ***importance affecting the*economy of all countries around the whole world.*******- To conduct intensive experiments on very large sets of data to discover new***ways of helping the social and economic well-being of our society.********