Grant: Discovery Grants Program - Individual
Concordia University
$48,000.00
Computational Analysis of Handwriting, Character Recognition, and Design of Digital Fonts
EF 2023-24
Résumé
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.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2019-07005
Name nom
Suen, Ching
Department département
Computer Science and Software Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2019
Award amount
48000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Information technology
Research subject en
Technologie de l'information
Research subject fr
Technologie de l'information
Application title
Computational Analysis of Handwriting, Character Recognition, and Design of Digital Fonts
Keyword
character recognition; design of digital fonts; digital fonts; fake coins; graphology; handwriting analysis; license plate
Application summary
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.