Cursive script recognition using wildcards and multiple experts
type: Item
instance of: scholarly article
title: Cursive script recognition using wildcards and multiple experts
zbMATH Open document ID: 0991.68660
author: A. Hennig
author: N. Sherkat
published in: PAA. Pattern Analysis and Applications
publication date: 2002-07-25T00:00:00Z
full work available at URL: 196415 467 Sherkat PrePublisher.pdf
review text: Variability in handwriting styles suggests that many letter recognition engines cannot correctly identify some handwritten letters of poor quality at reasonable computational cost. Methods that are capable of searching the resulting sparse graph of letter candidates are therefore required. The method presented here employs 'wildcards' to represent missing letter candidates. Multiple experts are used to represent different aspects of handwriting. Each expert evaluates closeness of match and indicates its confidence. Explanation experts determine the degree to which the word alternative under consideration explains extraneous letter candidates. Schemata for normalisation and combination of scores are investigated and their performance compared. Hill climbing yields near-optimal combination weights that outperform comparable methods on identical dynamic handwriting data.
Mathematics Subject Classification ID: 68U99
Mathematics Subject Classification ID: 68T10
zbMATH DE Number: 1771523
zbMATH Keywords: Dynamic handwriting data
zbMATH Keywords: Explanation expert
zbMATH Keywords: Multi-expert combination
zbMATH Keywords: Poor quality handwriting recognition
zbMATH Keywords: Self-confidence
zbMATH Keywords: Wildcard likelihood
zbMATH Keywords: Wildcards
MaRDI profile type: Publication
OpenAlex ID: W1972905627
DOI: 10.1007/S100440170024
description: scientific article; zbMATH DE number 1771523