DocumentCode
2513842
Title
Statistical Fourier Descriptors for Defect Image Classification
Author
Timm, Fabian ; Martinetz, Thomas
Author_Institution
Inst. for Neuro-& Bioinf., Univ. of Lubeck, Lübeck, Germany
fYear
2010
fDate
23-26 Aug. 2010
Firstpage
4190
Lastpage
4193
Abstract
In many industrial applications, Fourier descriptors are commonly used when the description of the object shape is an important characteristic of the image. However, these descriptors are limited to single objects. We propose a general Fourier-based approach, called statistical Fourier descriptor (SFD), which computes shape statistics in grey level images. The SFD is computationally efficient and can be used for defect image classification. In a first example, we deployed the SFD to the inspection of welding seams with promising results.
Keywords
Fourier transforms; image classification; statistical analysis; defect image classification; grey level images; object shape; shape statistics; statistical Fourier descriptors; welding seams; Correlation; Discrete Fourier transforms; Feature extraction; Inspection; Shape; Support vector machines; Welding; Defect Image Classification; Feature Extraction; Fourier Descriptors; Machine Vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location
Istanbul
ISSN
1051-4651
Print_ISBN
978-1-4244-7542-1
Type
conf
DOI
10.1109/ICPR.2010.1018
Filename
5597748
Link To Document