Title : 
A multi-font character recognition based on its fundamental features by artificial neural networks
         
        
            Author : 
Neves, E.M.de A. ; Gonzaga, Adilson ; Slaets, Annie France Frère
         
        
            Author_Institution : 
Inst. de Fisica de Sao Carlos, Brazil
         
        
        
        
        
        
            Abstract : 
Neural networks present an alternative approach for the character recognition problem. This paper describes the development of a recognition system of multi-font character using topological feature extraction to recognize capital isolated letters. By properly specifying a set of features such as vertical, horizontal, and slant strokes, curvature, open and closed areas, called here “fundamental features”, the recognition was performed using a backpropagation neural network
         
        
            Keywords : 
backpropagation; feature extraction; image classification; neural nets; optical character recognition; topology; artificial neural networks; backpropagation neural network; capital isolated letters; curvature; fundamental features; horizontal strokes; multi-font character recognition; slant strokes; topological feature extraction; vertical strokes; Artificial intelligence; Artificial neural networks; Character recognition; Feature extraction; Histograms; Humans; Neural networks; Optical character recognition software; Psychology; Text recognition;
         
        
        
        
            Conference_Titel : 
Cybernetic Vision, 1996. Proceedings., Second Workshop on
         
        
            Conference_Location : 
Sao Carlos
         
        
            Print_ISBN : 
0-8186-8058-X
         
        
        
            DOI : 
10.1109/CYBVIS.1996.629463