1 April 1993 Morphological hand-printed character recognition by a skeleton-matching algorithm
Panagiotis E. Trahanias, Konstantinos Stathatos, Fotios Stamatelopoulos, Emmanuel Skordalakis
Author Affiliations +
Abstract
We study the use of mathematical morphology for handprinted character recognition. Our approach uses the morphological skeleton transform as the shape descriptor. An efficient skeleton-matching algorithm, which renders the similarity between two skeletons as a distance measure, is employed. Based on this distance measure, a character is classified by a minimum distance classifier. The morphological skeleton transform contains complete shape information and is shown as a powerful descriptor for this class of shapes. We also study the pattern spectrum as a shape descriptor for handprinted characters. However, the pattern spectrum conveys only information about the shape/size distribution of a given object, which turns out to be not very efficient for hand-printed characters. Experimental results demonstrate the efficiency of the skeleton-based approach and the inadequacy of the pattern-spectrum-based approach.
Panagiotis E. Trahanias, Konstantinos Stathatos, Fotios Stamatelopoulos, and Emmanuel Skordalakis "Morphological hand-printed character recognition by a skeleton-matching algorithm," Journal of Electronic Imaging 2(2), (1 April 1993). https://doi.org/10.1117/12.143731
Published: 1 April 1993
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication and 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Distance measurement

Optical character recognition

Picosecond phenomena

Shape analysis

Shape memory alloys

Detection and tracking algorithms

Binary data

Back to Top