1999 · 42 citations · 10 references
ComputingComputer ScienceComputer VisionMachine LearningNatural Language ProcessingDocument Image AnalysisLetter RecognitionOptical Character RecognitionPattern RecognitionWord RecognitionCharacter ClassificationHandwriting RecognitionHandwritten Character RecognitionPrinted Text RecognitionStatistical Image FeaturesWritten Text
There are many types of documents where machine-printed and hand-written texts appear intermixed. Since the optical character recognition (OCR) methodologies for machine-printed and hand-written texts are different, it is necessary to separate these two types of text before feeding them to the respective OCR systems. In this paper, we present such a scheme for both Bangla and Devnagari characters. The scheme is based on the structural and statistical features of the machine-printed and hand-written text lines. The classification scheme has an accuracy of about 98.3%.
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Historical review of OCR research and development
S. Mori, Ching Y. Suen, Kazuhiko Yamamoto · Proceedings of the IEEE · 1992 · 869 citations
Kam‐Fai Wong, R. G. Casey, Friedrich M. Wahl · IBM Journal of Research and Development · 1982 · 590 citations