A Progressive Learning Method for Symbol Recognition
Дата
Авторы
Barrat,Sabine
Tabbone,Salvatore
Journal Title
Journal ISSN
Volume Title
Издатель
Journal of Universal Computer Science
Аннотация
Описание
This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propose a discriminant analysis method which provides allocation rules from a training set of labelled data. However a discriminant analysis method is efficient only if the training set and the test data are defined in the same conditions but it is rare in real life. In order to overcome this problem, a conditional vector is added to each instance to take into account the parasitic effects between the test data and the training set. We also propose an adaptation to consider the user feedback.
Ключевые слова
conditional discriminant analysis , symbol recognition