Weighted Principal Component Analysis Based Edge Linking


ÖZKAN K., IŞIK Ş.

International Symposium on Innovations in Intelligent SysTems and Applications (INISTA 2015), Madrid, Spain, 2 - 04 September 2015, pp.70-76 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/inista.2015.7276728
  • City: Madrid
  • Country: Spain
  • Page Numbers: pp.70-76
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

As a complicated and troublesome research area, the edge detection is a fundamental step in terms of some image processing tasks including segmentation, compression and registration. In this study, we present a new approach for edge linking by applying the concept of the PCA on different types of images to determine the attractive edge segments. To determine the direction by using the angle information, the PCA decomposition is carried out on the block around the processed point. Specifically, the horizontal and vertical directions are taken into account by considering the angle between the eigenvectors corresponding to the largest and smallest eigenvalues. After making some experiments on noisy and noise free images, we have observed that the proposed method is robust to noise, preserves the structure of image and extracts well-localized and straight lines.