DocumentCode :
2632161
Title :
Structural feature extraction on multiple bases with application to handwritten character recognition systems
Author :
Nishida, Hirobumi
Author_Institution :
Sch. of Comput. Sci. & Eng., Aizu Univ., Fukushima, Japan
fYear :
1993
fDate :
20-22 Oct 1993
Firstpage :
27
Lastpage :
30
Abstract :
H. Nishida and S. Mori (1992) proposed a clear, rigorous, and powerful method for the structural description of character shapes in terms of quasi-topological features (convexity and concavity), directional features, and singular points (branch points and crossings). Shapes are described by few components with rich features and shape prototypes (structural models) can be constructed automatically from the training data. However, the number of directions is fixed to 4, and more directions such as 8 or 16 cannot be dealt with. For various applications of Nishida and Mori´s method, the author presents a method for structural analysis and description of simple arcs or closed curves based on 2m (m = 2,3,4,...) directional features and convex/concave features. Software OCR systems without specialized hardware have attracted much attention recently. Based on the method of structural analysis and description, the author describes a software implementation of a handwritten character recognition system with a multi-stage strategy
Keywords :
feature extraction; handwriting recognition; optical character recognition; arcs; branch points; character shapes; closed curves; concavity; convexity; crossings; directional features; handwritten character recognition systems; multi-stage strategy; multiple bases; quasi-topological features; singular points; software OCR systems; structural analysis; structural description; structural feature extraction; training data; Application software; Character recognition; Computer science; Feature extraction; Handwriting recognition; Hardware; Optical character recognition software; Shape; Software systems; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Conference_Location :
Tsukuba Science City
Print_ISBN :
0-8186-4960-7
Type :
conf
DOI :
10.1109/ICDAR.1993.395789
Filename :
395789
Link To Document :
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