Paper Info
Title
E-spline sampling for precise and robust line-edge extraction
Abstract
We propose a line-edge extraction algorithm using E-spline functions as a sampling kernel. Our method is capable of extracting line-edge parameters, including amplitude, orientation, and offset, not only at sub-pixel level but also exactly provided noiseless pixel values. Even in noisy scenario, simulation results show that the proposed method outperforms a similar one based around B-spline functions with gains in standard deviation of 1.86dB for the orientation and 9.64dB for the offset when SNR is 10dB. We also show by simulations that our method extracts line-edges more precisely than the Hough transform.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652292
Image Processing
Keywords
Field
DocType
Hough transforms,edge detection,splines (mathematics),B-spline function,E-spline sampling function,Hough transform,noiseless pixel values,robust line edge parameter extraction,standard deviation,subpixel level,E-spline functions,Hough transform,Line-edge,finite rate of innovation signals
Spline (mathematics),Computer vision,Pattern recognition,Computer science,Edge detection,Signal-to-noise ratio,Hough transform,Robustness (computer science),Sampling (statistics),Artificial intelligence,Standard deviation,Offset (computer science)
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
4
PageRank 
References 
Authors
0.53
4
2
Name
Order
Citations
PageRank
Akira Hirabayashi11615.38
Dragotti, P.L.251239.29