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

手写计算分析、字符识别和数字字体设计

• 批准号: RGPIN-2019-07005
• 负责人: Suen, Ching
• 金额: $ 3.5万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=716126
• 关键词: Computational; Analysis; Handwriting; Character; Recognition

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.

在过去的几十年里，我们已经探索和开发了许多计算 识别不同类型模式的技术，包括但不限于 仅限于不同语言的手写，以及多种人类面孔， 年龄组这一发现补助金申请与新技术有关， 发现新知识 降低错误率的方法 优化不同识别算法的组合， 识别以英语、法语、阿拉伯语书写的字符和单词， 其他语言。它旨在改进我们的识别算法 通过结合新特征使用多级多分类器 在我们的速示镜和眼动追踪实验中发现， 这些年将 专注于我的研究的延伸， 以下 新领域 咨询笔迹学和心理学专家， 字体设计师： - 提取更详细的独特笔迹特征，例如 字符的形状、字符的形成方式和特性 个人的写作，以验证 相关性 笔迹和个性特征， 一个具有挑战性和 笔迹学中有争议的话题， 并检测他们的健康状况 作者，例如帕金森病和阿尔茨海默病患者。我们认为 我们在手写识别方面的丰富经验将使我们能够带来新的 深入了解这一主题，并提供帮助，以笔迹学家在节省他们的 是时候分析个人的笔迹了。 - 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易读性， 建议新的字体设计，以方便识别许可证 印版通过图像处理和模式识别技术来帮助 执法组织在寻找被盗汽车、交通违法行为、 识别车辆在不同的天气条件和指挥 of driven无人驾驶vehicles车辆. - 扩展我们的特征提取技术，例如关键点的提取 硬币上或钞票上的文字，以检测 伪钞 钱，这已成为一个迫在眉睫的问题， 影响的重要性 世界各国的经济。 - 对非常大的数据集进行密集的实验，以发现新的 帮助我们社会的社会和经济福祉的方法。