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Wood Knot Classification using Bagging

by S. Mohan, K. Venkatachalapathy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 51 - Number 18
Year of Publication: 2012
Authors: S. Mohan, K. Venkatachalapathy
10.5120/8146-1937

S. Mohan, K. Venkatachalapathy . Wood Knot Classification using Bagging. International Journal of Computer Applications. 51, 18 ( August 2012), 50-53. DOI=10.5120/8146-1937

@article{ 10.5120/8146-1937,
author = { S. Mohan, K. Venkatachalapathy },
title = { Wood Knot Classification using Bagging },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 51 },
number = { 18 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 50-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume51/number18/8146-1937/ },
doi = { 10.5120/8146-1937 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:51:08.263272+05:30
%A S. Mohan
%A K. Venkatachalapathy
%T Wood Knot Classification using Bagging
%J International Journal of Computer Applications
%@ 0975-8887
%V 51
%N 18
%P 50-53
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The quality of the wood is determined by the number of defects and its distribution. In a piece of timber, the most common type of imperfection is called knot that decreases the strength of the wood. Manual selection and classification process of knots is tedious and time consuming job. An automatic sensing machine is able to inspect wood automatically and correctly identify the defects it possess, and its effect on the quality of the final product. In this paper, it is proposed to detect and classify the knots in timber boards. The image of knots is pre processed using Hilbert transform and Gabor filters. The features obtained from pre processing, is classified using data mining techniques and compared with bagging technique.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Wood Knots Hilbert Transforms Gabor Filter Naïve Bayes Radial Basis Function

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