title:
 
Apriori Data Mining on Rotationally Invariant Multiresolutional Moments for Pattern Recognition
publication:
 
JCIS-2006 Proceedings
part of series:
  Advances in Intelligent Systems Research
ISBN:
  978-90-78677-01-7
ISSN:
  1951-6851
DOI:
  doi:10.2991/jcis.2006.260 (how to use a DOI)
author(s):
 
Annupan Rodtook, Stanislav Makhanov
corresponding author:
 
Annupan Rodtook
publication date:
 
October 2006
keywords:
 
filter bank, the Kullback-Leibler distance, Apriori mining algorithm, fuzzy C-mean clustering
abstract:
 
We propose a new feature selection procedure based on a combination of a pruning algorithm, Apriori mining techniques and fuzzy C-mean clustering. The feature selection algorithm is designed to mine on a multiresolution filter bank composed of rotationally invariant moments. The numerical experiments, with more than 10,000 images, demonstrate an accuracy increase of about 5% for a low noise, 15% for an average noise and 20% for a high-level noise.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
full text: