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识别不同类型模式的计算*技术，包括但不限于*不同语言的手写，以及多个*年龄段的人脸。这项发现奖励申请涉及*发现新的基于知识的**特征的新技术，降低错误率*和优化不同识别算法组合的方法，以及*以英语、法语、阿拉伯语和*其他语言书写的字符和单词的识别。它的目的是通过结合我们在过去几年*的速测仪和眼睛跟踪实验中发现的新特征*来改进我们的识别算法*使用多级多分类器。我的研究将集中在以下*新领域*咨询笔迹学和心理学专家、*和字体设计师*--提取更详细的有特色的笔迹特征，如字符的*形状、形成方式和个人书写的特点*，以验证*笔迹与个性特征之间的**相关性，这在笔迹学中是一个具有挑战性和*争议的话题，**并检测*作者的健康状况，例如，那些患有帕金森症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个主题带来新的*见解，并为字学家节省*分析个人笔迹的*时间提供帮助。*-应用我们的字符识别和感知技术来评估*汽车牌照中使用的字体的可读性，并*提出新的字体设计，以便于通过图像处理和模式识别技术来识别车牌*，以帮助*执法机构寻找被盗汽车、交通违章、*不同天气条件下的识别车辆和无人驾驶车辆的指挥*。*-扩展我们的特征提取技术，如提取硬币上或钞票上印制的字符的关键点*，以检测*假币和纸币**，这已经成为一个影响世界各国经济的迫在眉睫的课题。*-对非常庞大的数据集进行密集的实验，以发现帮助我们社会和经济福祉的新*方法。*

***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.********