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Proceedings Paper

Offline recognition of handwritten cursive words
Author(s): John T. Favata; Sargur N. Srihari
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Paper Abstract

A robust algorithm for offline cursive script recognition is described. The algorithm uses a generate-and-test paradigm to analyze cursive word images. The generate phase of the algorithm intelligently segments the word after analyzing certain structural features present in the word. The test phase determines the most likely character candidates among the segmentation points by using a recognition algorithm trained on generalized cursive letter shapes. In a sense, word recognition is done by sliding a variable sized window across the word looking for recognizable characters and strokes. The output of this system is a list of all plausible interpretations of the word. This list is then analyzed by a two-step contextual post- processor which first matches all of the interpretations to a supplied dictionary using a string matching algorithm. This eliminates the least likely interpretations. The remaining candidates are then analyzed for certain character spatial relationships (local reference line finder) to finally rank the dictionary. The system has the advantage of not requiring explicit word training yet is able to recognize many handwriting styles. This system is being successfully tested on a database of handwritten words extracted from live mail with dictionary sizes of up to 300 words. Planned extensions include developing a multilevel generate-and-test paradigm which can handle any type of handwritten word.

Paper Details

Date Published: 1 August 1992
PDF: 11 pages
Proc. SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, (1 August 1992); doi: 10.1117/12.130290
Show Author Affiliations
John T. Favata, SUNY/Buffalo (United States)
Sargur N. Srihari, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 1661:
Machine Vision Applications in Character Recognition and Industrial Inspection
Donald P. D'Amato; Wolf-Ekkehard Blanz; Byron E. Dom; Sargur N. Srihari, Editor(s)

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