Title :
A multiple-classifier system for recognition of printed mathematical symbols
Author :
Garain, Utpal ; Chaudhuri, B.B. ; Ghosh, R.P.
Author_Institution :
Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India
Abstract :
This paper deals with recognition of printed mathematical symbols. A group of classifiers arranged hierarchically is used to achieve robust recognition of the large number of symbols appearing in expressions. The classifier used at the top level employs stroke-based classification technique to recognize some of the frequently occurring symbols. The second level uses three classifiers to recognize the rest of the expression symbols. Different combination techniques have been attempted to integrate the second level classifiers to achieve high recognition accuracy. Experiment shows that the proposed approach is quite robust for recognition of a large number of symbols appearing in various expressions.
Keywords :
character recognition; document image processing; feature extraction; image classification; image segmentation; feature extraction; image segmentation; multiple classifier system; printed mathematical symbol recognition; robust recognition; stroke based classification technique; Character recognition; Computer science; Computer vision; Feature extraction; Handwriting recognition; Pattern recognition; Robustness; Shape; Testing; Typesetting;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334131