Offline grammar-based recognition of handwritten sentences

Zimmermann, Matthias; Chappelier, Jean-Cédric; Bunke, Horst (2006). Offline grammar-based recognition of handwritten sentences. IEEE transactions on mobile computing, 28(5), pp. 818-821. Los Alamitos, Calif.: IEEE Computer Society 10.1109/TPAMI.2006.103

01608043.pdf - Published Version
Available under License Publisher holds Copyright.
© 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Download (601kB) | Preview

This paper proposes a sequential coupling of a Hidden Markov Model (HMM) recognizer for offline handwritten English sentences with a probabilistic bottom-up chart parser using Stochastic Context-Free Grammars (SCFG) extracted from a text corpus. Based on extensive experiments, we conclude that syntax analysis helps to improve recognition rates significantly.

Item Type: Journal Article (Original Article)
Division/Institute: 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor: Bunke, Horst
Subjects: 000 Computer science, knowledge & systems
500 Science > 510 Mathematics
ISSN: 1536-1233
Publisher: IEEE Computer Society
Language: English
Submitter: Factscience Import
Date Deposited: 04 Oct 2013 14:45
Last Modified: 12 Dec 2014 09:53
Publisher DOI: 10.1109/TPAMI.2006.103
PubMed ID: 16640266
Web of Science ID: 000235885700012
Uncontrolled Keywords: Optical character recognition, handwriting analysis, natural language parsing and understanding
BORIS DOI: 10.7892/boris.18491
URI: (FactScience: 637)

Actions (login required)

Edit item Edit item
Provide Feedback