Award Date
1-1-2005
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Committee Member
Evangelos Yfantis
Number of Pages
49
Abstract
This research mainly focuses on recognizing the handwritten characters on a form in order to automate the Medical Form processing. Several efficient algorithms have been developed by us so far, to separate the handwritten characters from printed text character; to separate the lines, words and each character. In this thesis, we concentrate on the recognition of the segmented handwritten characters. Different feature recognition algorithms are employed and their performance on a given training set is analyzed. We find a way to combine all these individual feature recognition algorithms by incorporating their interdependence. The reliability of these algorithms is determined in terms of Conditional Probabilities and a rule for classifying the input character based on the outputs of each individual feature recognition algorithms is identified from the observations.
Keywords
Character; Combining; Conditional; Handwritten; Multiple; Probabilities; Recognition; Recognizers
Controlled Subject
Computer science
File Format
File Size
1351.68 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Permissions
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Repository Citation
Padmanaban, Mageshkumar, "Handwritten character recognition by combining multiple recognizers using conditional probabilities" (2005). UNLV Retrospective Theses & Dissertations. 1896.
http://dx.doi.org/10.25669/yi65-9jpi
Rights
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