DocumentCode :
2168714
Title :
A system for segmentation and recognition of totally unconstrained handwritten numeral strings
Author :
Shi, Z. ; Srihari, S.N. ; Shiu, Y.-C. ; Ramanaprasad, V.
Author_Institution :
Center of Excellence for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA
Volume :
2
fYear :
1997
fDate :
18-20 Aug 1997
Firstpage :
455
Abstract :
Proposes a system for the segmentation and recognition of totally unconstrained handwritten numeral strings. The system is composed of several document analysis modules, namely a preprocessing module, a segmentation module and a recognition module. The preprocessing module includes connected component analysis, identifying substrings with touching digits and estimating the number of digits in the substring. The segmentation module is built with a new segmentation algorithm based on a thorough stroke analysis using contour representation of the strokes. In the recognition module, a high-performance digit recognizer is used for the isolated digit images after segmentation, and then a simple postprocessing routine is called for those cases where some punctuation marks or delimiters such as dashes, commas or periods are included in the numeral string. Due to the high performance of the segmentation module, the system is efficient and robust with a high recognition performance
Keywords :
document image processing; handwriting recognition; image segmentation; optical character recognition; software performance evaluation; subroutines; character recognition; connected component analysis; contour representation; delimiters; digit number estimation; document analysis modules; high-performance digit recognizer; isolated digit images; postprocessing routine; preprocessing module; punctuation marks; recognition module; recognition performance; segmentation module; string segmentation; stroke analysis; substring identification; totally unconstrained handwritten numeral strings; touching digits; Algorithm design and analysis; Handwriting recognition; Image recognition; Image segmentation; Robustness; Text analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location :
Ulm
Print_ISBN :
0-8186-7898-4
Type :
conf
DOI :
10.1109/ICDAR.1997.620538
Filename :
620538
Link To Document :
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