Model-based shape matching with structural feature grouping

Author

Nishida, Hirobumi

Author_Institution

Sch. of Comput. Sci. & Eng., Aizu Univ., Fukushima, Japan

Volume

17

Issue

3

fYear

1995

fDate

3/1/1995 12:00:00 AM

Firstpage

315

Lastpage

320

Abstract

An essential problem in online handwriting recognition is the shape variation along with the variety of stroke number and stroke order. In this paper we present a clear and systematic approach to shape matching based on structural feature grouping. To cope with topological deformations caused by stroke connection and breaking, we incorporate some aspects of top-down approaches systematically into the shape matching algorithm. The grouping of local structural features into high-level features is controlled by high-level knowledge as well as the simple geometric conditions. The shape matching algorithm has the following properties from the viewpoint of online character recognition: (1) stroke order, direction, and number are free, and (2) stroke connection and breaking are allowed

Keywords

feature extraction; handwriting recognition; image matching; high-level knowledge; model-based shape matching; online character recognition; online handwriting recognition; stroke breaking; stroke connection; structural feature grouping; top-down approaches; topological deformations; Character recognition; Computer science; Couplings; Handwriting recognition; Image analysis; Image matching; Image recognition; Keyboards; Prototypes; Shape;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.368198

Filename

368198