Automatic Discrimination between Printed and Handwritten Text in Documents

Recognition techniques for printed and handwritten text in scanned documents are significantly different. In this paper we address the problem of identifying each type. We can list at least four steps: digitalization, preprocessing, feature extraction and decision or classification. A new aspect of...

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Bibliographic Details
Published in2009 XXII Brazilian Symposium on Computer Graphics and Image Processing pp. 261 - 267
Main Authors da Silva, Lincoln Faria, Conci, Aura, Sanchez, Angel
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Character recognition
Classification tree analysis
Computer graphics
Data mining
document analysis
Feature extraction
Hidden Markov models
Image databases
Image processing
Image segmentation
Machine Vision
Optical character recognition software
optical characters recognition
text identification
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ISBN1424449782
9781424449781
ISSN1530-1834
DOI10.1109/SIBGRAPI.2009.40

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Summary:Recognition techniques for printed and handwritten text in scanned documents are significantly different. In this paper we address the problem of identifying each type. We can list at least four steps: digitalization, preprocessing, feature extraction and decision or classification. A new aspect of our approach is the use of data mining techniques on the decision step. A new set of features extracted of each word is proposed as well. Classification rules are mining and used to discern printed text from handwritten. The proposed system was tested in two public image databases. All possible measures of efficiency were computed achieving on every occasion quantities above 80%.
ISBN:1424449782
9781424449781
ISSN:1530-1834
DOI:10.1109/SIBGRAPI.2009.40