Morphological corner detector using paired triangular structuring elements

  • Authors:

  • Alina Sobania;J. Paul O. Evans

  • Affiliations:

  • Vision Systems Group, School of Computing and Informatics, Nottingham Trent University, Newton Building, Burton Street, Nottingham NG1 4BU, UK;Vision Systems Group, School of Computing and Informatics, Nottingham Trent University, Newton Building, Burton Street, Nottingham NG1 4BU, UK

  • Venue:
  • Pattern Recognition
  • Year:
  • 2005

Quantified Score

Hi-index 0.01

Visualization

Abstract

This paper describes corner detection from segmented areas using mathematical morphology employing paired triangular structuring elements. The algorithm identified as TriSE02 detects the inner corners of a segmented area and stores information regarding each corner's angular orientation and position. The theoretical development of this detector together with its empirical performance is established in a test utilising standard template images. Seven other established corner detectors were also tested to provide comparative performance information. This work was originally developed to identify conjugate corners in stereoscopic dual-energy X-ray images produced by an experimental system for aviation security screening. The oversensitivity exhibited by the established detectors when applied to the dual-energy X-ray images has been significantly improved upon by the new detector. Also, the careful development of the default parameterisation has resulted in a flexible approach, which is suitable for different image types and formats.