FSA-Based Optimal Segmentation for Camera-Based CharacterRecognition
Journal
Proceedings of MIRU 2006
Presentation number
IS3-2
Pages
pp.1024-1029
Reviewed
Not reviewed
Date
July 2006
Research fields
Pattern recognition
Key
Sakai2006 (id=846)
Abstract
For accurate camera-based character recognition, a method where category information is embedded
onto every character image as a striped pattern has been investigated. The cross ratio calculated from the widths of
stripes represents the category of the character. In this paper, an algorithm to detect the boundaries of the stripes
for measuring the widths is proposed. The algorithm is realized by a combination of a dynamic programming-based
optimal segmentation framework and a finite state automaton (FSA) which represents the characteristics of the
striped pattern. Experimental results showed the ability of the proposed method on not only accurate boundary
detection but also accurate recovery of the embedded cross ratio.
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