Abstract

This paper describes techniques to separate a line of unconstrained (written in a natural manner) handwritten text into words. When the writing style is unconstrained, recognition of individual components may be unreliable so they must be grouped together into word hypotheses, before recognition algorithms (which may require dictionaries) can be used. Our system uses original algorithms to determine distances between components in a text line and to detect punctuation. The algorithms are tested on nearly 3000 handwritten text lines extracted from postal address blocks. We give a detailed performance analysis of the complete system and its components. Key Words: text understanding , pattern recognition , handwritten text recognition 1. INTRODUCTION This research focuses on separating a line of handwritten text into words by determining the location of inter-word gaps (gaps between words). This paper describes and evaluates distance measurement algorithms, punctuation detection algorith...

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