Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/1540

Title

Analysis and recognition of broken handwritten digits based on skeleton and morphological structure

Author(s)

Yu, Donggang;  Lai, Wei

Abstract

This paper presents an efficient method of reconstructing and recognizing broken handwritten digits. Constrained dilation algorithms are used to bridge small gaps and smooth some spurious points. The contours of broken handwritten digits are smoothed and linearized, and a set of structural points of digits are detected along the outer contours of digits. These structural points are used to describe the morphological structure of broken digits. The broken digits are skeletonized with an improved thinning algorithm. Spurious segments introduced during the extraction of digit fields are detected and deleted based on the structure analysis of digit fields, segment recognition, segment extension, skeleton structure and geometrical features. The broken points of the digits are preselected based on the minimum distance between the \end" points of skeletons of two neighboring regions. The correction rules of the preselected broken points are also based on the structure analysis and comparison of broken digits. Experimental results showing the effectiveness of the method are given.

Publication type

Journal article

Research centre

Swinburne University of Technology. School of Information Technology

Source

International Journal of Pattern Recognition and Artificial Intelligence, Vol. 19, no. 3 (2005), pp. 271-296

Publication year

2005

Publisher

World Scientific Publishing Company Pty Ltd

Format

pp. 271-296

ISSN

0218-0014

Publisher URL

International Journal of Pattern Recognition and Artificial Intelligence

Publisher URL

http://dx.doi.org/10.1142/S0218001405004095

Copyright

© World Scientific Publishing Company.

Peer reviewed