Paper Info
Title
Use of an Evolutive Base of Models in a System for Reading Printed Texts
Abstract
The recognition system of printed text that we are presenting uses a base of models of characters to recognize the prototypes of various patterns of characters encountered in successive readings. To identify the prototypes, we have developed a decision making method based on the use of adaptive adherences borrowed from the rule of pretopology [1][2]. This approach which we have termed adaptable epsilon(x)-neighbors allows an adjustment of classes using a minimum quantity of information. To reorganize the representation space, we have elaborated a system in which the models are associated to weights for which a continuous correction process is conducted This process effects a permanent evolution of the models and continuously questions their influence in recognition. Weight management that entails the creation and the removal of models places our system in a context of continuous leading.
Year
DOI
Venue
1998
10.1109/ICPR.1998.711269
ICPR
Keywords
Field
DocType
printed texts,evolutive base,weight management,decision theory,prototypes,context modeling,learning artificial intelligence,read only memory,tail
Computer vision,Read-only memory,Recognition system,Character recognition,Computer science,Context model,Decision theory,Artificial intelligence
Conference
ISSN
ISBN
Citations 
1051-4651
0-8186-8512-3
0
PageRank 
References 
Authors
0.34
2
1
Name
Order
Citations
PageRank
Jean-luc Henry1123.13