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

在过去的几十年里，我们已经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笔迹，以及多个年龄组的人脸。这项发现资助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。它旨在通过结合过去几年在速视镜和眼动追踪实验中发现的新特征，改进我们使用多阶段多分类器的识别算法。在与笔迹学、心理学和字体设计专家的协商下，我的研究将集中在以下新领域的延伸：-提取更详细的笔迹特征，如汉字的形状、汉字的形成方式和个人的书写特点，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，并检测写信人的健康状况，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，并帮助笔迹学家节省分析个人笔迹的时间。-运用我们的字符识别和感知技术，评估汽车牌照字体的易读性，并提出新的字体设计，以方便使用图像处理和模式识别技术识别车牌，以协助执法机关查找被盗车辆、交通违例事项、识别不同天气情况下的车辆和指挥无人驾驶车辆。-扩展我们的特征提取技术，例如提取硬币或钞票上铸造的字符关键点，以检测假币和纸币，这已成为影响世界各国经济的迫在眉睫的重要课题。-在庞大的数据集上进行深入的实验，以发现有助于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.