Paper Info
Title
Sub-pixel edge detection for photogrammetry using laplace difference of Gaussian and 4th order ENO interpolation
Abstract
In modern photogrammetry for structure health monitoring, the detection of retro reflective targets, play a vital role in the accurate measurement of structural objects. However, due to the limitation of the resolution in photogrammetric equipment, a sufficient accuracy may not be achievable. While existing sub-pixel interpolation techniques may be used to overcome this limitation, they may produce unreliable results when presented with weak edge points. This paper presents a new sub-pixel edge detection algorithm namely, the ENO-LDoG method, which incorporates a high-order ENO interpolation scheme and a Laplace of a difference of Gaussian to accurately determine edge points. Experimental results on sample targets show that a higher precision can be achieved when compared to existing methods.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652041
Image Processing
Keywords
Field
DocType
Gaussian processes,Laplace transforms,condition monitoring,edge detection,interpolation,ENO interpolation,Gaussian interpolation,Laplace difference,photogrammetry,structure health monitoring,sub-pixel edge detection,photogrammetry,structural health monitoring,sub-pixel edge detection
Photogrammetry,Computer vision,Edge detection,Computer science,Interpolation,Artificial intelligence,Condition monitoring,Pixel,Gaussian process,Image resolution,Difference of Gaussians
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Laurence Pap100.34
Ju Jia Zou219820.00