Title : ( A note on neurofractal-based defect recognition and classification in nonwoven web images )
Authors: Pedram Payvandy , M. Yousefzadeh-Chimeh , M. Latifi ,
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Abstract
This paper introduces the off-line neurofractal method developed for defect detection and classification in thermal-bond nonwoven web images using box counting dimension as feature extractor and backpropagation neural network algorithm as defect classifier. The results of applying the proposed methodology on nonwoven web images show that defects are recognized and classified with high accuracy.
Keywords
nonwoven; defect; recognition; classification; fractal box counting; neural network; image analysis
@article{paperid:1105254,
author = {Pedram Payvandy, and مریم یوسف زاده and مسعود لطیفی},
title = {A note on neurofractal-based defect recognition and classification in nonwoven web images},
journal = {The Journal of The Textile Institute},
year = {2010},
volume = {101},
number = {1},
month = {January},
issn = {0040-5000},
pages = {46--51},
numpages = {5},
keywords = {nonwoven; defect; recognition; classification; fractal box counting; neural network; image analysis},
}
%0 Journal Article
%T A note on neurofractal-based defect recognition and classification in nonwoven web images
%A Pedram Payvandy,
%A مریم یوسف زاده
%A مسعود لطیفی
%J The Journal of The Textile Institute
%@ 0040-5000
%D 2010
