Recognition of unconstrained handwritten numeral strings using decision value generator

This paper presents recognition of unconstrained handwritten numeral strings using a decision value generator. The numeral string recognition system is composed of three modules: pre-segmentation, segmentation and recognition. The pre-segmentation module classifies a numeral string into sub-images,...

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Bibliographic Details
Main Authors: Kye Kyung Kim, Yun Koo Chung, Jin Ho Kim, Suen, C.Y.
Format: Conference Proceeding
Language:English
Subjects:
Handwriting recognition
Merging
NIST
Pattern recognition
Postal services
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Summary:This paper presents recognition of unconstrained handwritten numeral strings using a decision value generator. The numeral string recognition system is composed of three modules: pre-segmentation, segmentation and recognition. The pre-segmentation module classifies a numeral string into sub-images, such as isolated digits, touching digits or broken digits, based on the confidence value of decision value generator. The segmentation module splits the touching digits using the reliability value of decision value generator. Both segmentation-based and segmentation free methods are used in classification and segmentation. To evaluate the proposed method, experiments were conducted using the handwritten numeral strings of NIST SD19 and a higher recognition performance than previous works was obtained.
DOI:10.1109/ICDAR.2001.953746