Abstract
This paper presents an approach to text recognition which avoids the problems of thresholding and segmentation by working directly on the grey-level image recognizing an entire word at the time. For each word a sequence of grey-level feature vectors is extracted. Hidden Markov models are used to describe the single characters and the sequence of feature vectors is matched against all possible combinations of models using dynamic programming.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
