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

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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.