Title :
Model-based shape matching with structural feature grouping
Author :
Nishida, Hirobumi
Author_Institution :
Sch. of Comput. Sci. & Eng., Aizu Univ., Fukushima, Japan
fDate :
3/1/1995 12:00:00 AM
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;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on