A fuzzy ARTMAP module for graphics symbols recognition

Author

Murshed, Nabeel A. ; Bortolozzi, Flavio

Author_Institution

LADIANN, Pontificia Univ. Catolica do Parana, Curtiba, Brazil

Volume

3

fYear

1998

fDate

4-9 May 1998

Firstpage

1700

Abstract

This paper presents a method for recognizing graphics symbols of electronic components in a database of circuit layouts. The method is based on the one-class problem approach on our ability to recognize a 2D-objects without making an explicit decomposition. To satisfy these requirements, a fuzzy ARTMAP recognition module was developed with the objective of recognizing the graphics symbols of 19 electronic components. Each fuzzy ARTMAP was trained with 2D images of graphic symbols of one component only (positive patterns only). The recognition module was then used to search for a specific component in a database of 30 images of circuit layouts. The training and test sets contained respectively, 380 images (2D images/component), and 2051 images (an average of 108 images/component). Experimental results show an average percentage error of 3.49%

Keywords

ART neural nets; circuit diagrams; circuit layout CAD; document image processing; fuzzy neural nets; image recognition; visual databases; 2D object recognition; circuit layouts; database; electronic components; fuzzy ARTMAP module; graphics symbols recognition; neural net; one-class problem; Circuits; Graphics; Image analysis; Image databases; Image recognition; Layout; Neural networks; Pattern recognition; Shape; Text analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.687112

Filename

687112