Title
Weighted principal component analysis based edge linking
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.
Year
DOI
Venue
2015
10.1109/INISTA.2015.7276728
2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)
Keywords
Field
DocType
edge detection,angle information with PCA,edge linking
Canny edge detector,Image gradient,Pattern recognition,Image texture,Edge detection,Range segmentation,Image processing,Image segmentation,Artificial intelligence,Morphological gradient,Mathematics
Conference
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
Kemal Özkan141.73
Sahin Isik243.42