Paper
24 July 2000 FFT-descriptors for shape recognition of military vehicles
Andreas Wimmer, Georg S. Ruppert, Oliver Sidla, Harald Konrad, Floris M. Gretzmacher
Author Affiliations +
Abstract
An accurate method to detect and classify military vehicles based on the recognition of shapes is presented in this work. FFT-Descriptors are used to generate a scale, translation and rotation invariant characterization of the shape of such an object. By interpreting the boundary pixels of an object as complex numbers it is possible to calculate an FFT-Descriptor based on the spectrum of a Fast Fourier Transform of these numbers. It is shown that by using this characterization it is possible to match such representations with models in a database of known vehicles and thereby gaining a highly robust and fault tolerant object classification. By selecting a specific number of components of a FFT-Descriptor the classification process can by tailored to different needs of recognition accuracy, allowed shape deviation and classification speed.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andreas Wimmer, Georg S. Ruppert, Oliver Sidla, Harald Konrad, and Floris M. Gretzmacher "FFT-descriptors for shape recognition of military vehicles", Proc. SPIE 4029, Targets and Backgrounds VI: Characterization, Visualization, and the Detection Process, (24 July 2000); https://doi.org/10.1117/12.392514
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Databases

Sensors

Image segmentation

Fourier transforms

Cameras

Object recognition

Video

RELATED CONTENT

Querying multiple-perspective video
Proceedings of SPIE (December 17 1998)
Real-time high-level video understanding using data warehouse
Proceedings of SPIE (February 15 2006)
VISTA data flow system: status
Proceedings of SPIE (June 29 2006)
Using a priori data for prediction and object recognition in...
Proceedings of SPIE (September 30 2003)

Back to Top