Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234272
Title: Algorithms for the recognition of handwriting in real-time
Author: Wright, Philip Timothy
ISNI:       0000 0004 2666 3048
Awarding Body: Council for National Academic Awards
Current Institution: Nottingham Trent University
Date of Award: 1989
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Abstract:
This thesis details the work undertaken by the author from September 1984 to September 1988 into the field of dynamic script recognition. It reviews the various techniques developed since 1960 and it analyses the more popular approaches to processing the raw pen motion information. It also details the progress made in the nature of the user interface over the last 28 years. The main emphasis of the work has been the development of algorithms capable of recognising, in a real-time user independent environment, lower case hand-printing. In particular, the design of the character shape databases provides for rapid searching and character matching and the techniques of feature reduction provide character matches to be found from previously original character encodings. The most successful algorithm, based on the method of curve encoding by H. Freeman, forms a foundation towards the development of natural user text and data entry system. Extension of the character base is also possible with no alteration to the basic algorithm methodology. A technique of robust word segmentation has been designed that has enabled the design of a prototype cursive script recognition system. This is presently writer independent, running on a 68020 micro-processor. Initial results show a word level recognition rate of 95+ %. Development of natural editing functions provides a self contained text entry environment. In the future, the algorithms will be ported to an 'electronic paper' environment and a user training phase will be designed as a front end to the recogniser.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.234272  DOI: Not available
Keywords: Computer recognition of script
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