A system for segmentation and recognition of totally unconstrained handwritten numeral strings

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.

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