Statistical Fourier Descriptors for Defect Image Classification

Fabian Timm, Thomas Martinetz

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.
Original languageEnglish
Title of host publicationProceedings of the 20th Int. Conference on Pattern Recognition (ICPR)
Number of pages4
PublisherIEEE
Publication date07.10.2010
Pages4190-4193
ISBN (Print)978-1-4244-7542-1
ISBN (Electronic)978-1-4244-7541-4
DOIs
Publication statusPublished - 07.10.2010
Event2010 20th International Conference on Pattern Recognition - Istanbul, Turkey
Duration: 23.08.201026.08.2010

Fingerprint

Dive into the research topics of 'Statistical Fourier Descriptors for Defect Image Classification'. Together they form a unique fingerprint.

Cite this