Gaussian Rule Based Fuzzy (GRBF) Membership Edge Detection on Hand Phantom Radiograph Images

  • Authors:
  • Noor Elaiza Abdul Khalid;Mazani Manaf;Mohd Ezane Aziz;Noorhayati Mohamed Noor;Norsyuhaiza Zainol

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • CGIV '08 Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper introduces the Gaussian shaped membership function to refine the Rule Based Fuzzy (RBF) image detection. It is expected that the proposed algorithm Gaussian Rule Based Fuzzy (GRBF) method can further refined the detection of periosteal and endosteal edges of hand phantom radiographs. The experimental data consists of four sets of hand phantom radiograph. Only metacarpal 2, 3 and 4 are considered. All of these data are processed with both GRBF and RBF. Mean and median filters are used as preprocessing tools. The results are compared both subjectively and statistically. The periosteal (strong edges) are well detected by both RBF and GRBF. However GRBF performs better than RBF in detecting the endosteal edges (weak edges).