Paper Info
Title
Fast affine transform for real-time machine vision applications
Abstract
In this paper, we have proposed a fast affine transform method for real-time machine vision applications. Inspection of parts by machine vision requires accurate, fast, reliable, and consistent operations, where the transform of visual images plays an important role. Image transform is generally expensive in computation for real-time applications. For example, a transform including rotation and scaling would require four multiplications and four additions per pixel, which is going to be a great burden to process a large image. Our proposed method reduces the complexity substantially by removing four multiplications per pixel, which exploits the relationship between two neighboring pixels. In addition, this paper shows that the affine transform can be performed by fixed point operations with marginal error. Two interpolation methods are also tried on top of the proposed method in order to test the feasibility of fixed point operations. Experimental results indicated that the proposed algorithm was about six times faster than conventional ones without any interpolation and five times faster with bilinear interpolation.
Year
DOI
Venue
2006
10.1007/11816157_147
ICIC (1)
Keywords
Field
DocType
fixed point operation,bilinear interpolation,interpolation method,large image,machine vision,fast affine,real-time application,real-time machine vision application,proposed algorithm,neighboring pixel,real time,affine transformation,fixed point
Affine transformation,Computer vision,Machine vision,Computer science,Interpolation,Image processing,Algorithm,Multiplication,Artificial intelligence,Pixel,Fixed point,Bilinear interpolation
Conference
Volume
ISSN
ISBN
4113
0302-9743
3-540-37271-7
Citations 
PageRank 
References 
2
0.38
3
Authors
4
Name
Order
Citations
PageRank
Sunyoung Lee1154.20
Gwang-Gook Lee2474.63
Euee S. Jang34015.77
Whol-Yul Kim420.38