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

在过去的几十年里，我们探索和开发了大量的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笔迹，以及多个年龄段的人脸。这项发现奖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，以及用英语、法语、阿拉伯语和其他语言书写的字符和单词的识别。它的目的是通过整合过去几年在测速仪和眼球跟踪实验中发现的新特征，来改进我们使用多级多分类器的识别算法。它将集中在以下新领域的研究上，咨询笔迹学和心理学专家，以及字体设计师：-提取更详细的独特笔迹特征，如字符的形状、字符的形成方式，以及个人笔迹的特殊性，验证笔迹和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主题，并检测作者的健康状况，例如帕金森和阿尔茨海默病患者。我们相信，我们在笔迹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，并为笔迹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车牌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识别车牌，以帮助执法机构发现被盗汽车、交通违法行为、识别不同天气条件下的车辆和指挥无人驾驶车辆。-扩展我们的特征提取技术，如对铸造在硬币上或印在钞票上的字符的关键点进行快速提取，以检测假币和纸币，这已成为影响全球各国经济的迫在眉睫的重要课题。-对非常庞大的数据集进行密集实验，以进一步发现帮助我们社会经济福祉的新方法。

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.