SciELO - Scientific Electronic Library Online

 
vol.9 issue1Theoretic-Experimental Analysis of Comparison Criteria for Object-Oriented Conceptual SchemasImplementation of a Neural Hierarchical Multimodel for Identification and Control of Mechanical Systems author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

Print version ISSN 1405-5546

Abstract

RAMIREZ ALONSO, Graciela María de Jesús  and  CHACON MURGUIA, Mario Ignacio. Wood Defects Classification Using Artificial Neural Network. Comp. y Sist. [online]. 2005, vol.9, n.1, pp.17-27. ISSN 1405-5546.

This paper describes a neural classifier to classify 7 different wood defects called knots. Human visual inspection of these defects involves a high degree of complexity due to inter-class variance. 2D Gabor filters were used for feature extraction. These filters are selective band pass filters to orientation and frequency. These filters are used where texture is an important feature. The method of principal component analysis was used to reduce the number of features generated by the Gabor filters. The neural network implemented was a multilyer perceptron with 3 layers trained with the Resalient backpropagation algorithm. The performance of the classifier was 83.91% of correct classification. This result is acceptable considering that the performance of a human inspector is 75% to 85%.

Keywords : Neural networks; Gabor filters; image processing.

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License