Recognition of Container Code Characters through Gray-Level Feature Extraction and Gradient-Based Classifier Optimization

Authors:
M. Goccia;M. Bruzzo;C. Scagliola;S. Dellepiane
Affiliations:
-;-;-;-
Venue:
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Year:
2003

Citing 6
Cited 2

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Abstract

This paper describes the recognition of container codecharacters in the project Mocont-II, where containerimages are taken in largely varying light situations. Therecognition system has to deal with gray-level charactersshowing a wide variability of brightness and contrast,varying inclination, segmentation uncertainties, damagedcharacters and the presence of shadows. Different sets offeatures were extracted directly from gray-level images,and a minimum distance classifier with a weighted metricwas used for recognition. To achieve good recognitionperformances, the feature weights and the prototype setswere optimized by a new gradient-based learningalgorithm that maximizes a fuzzy recognition ratefunctional.