Log-polar transform-based wavelet-modified maximum average correlation height filter for distortion-invariant target recognition
| Autor: | Vinod K. Beri, Amit Aran, Naveen K. Nishchal, Arun K. Gupta |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Log polar
business.industry Mechanical Engineering Wavelet transform Invariant (physics) Scale invariance Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials Correlation Wavelet Optical correlator Computer vision Artificial intelligence Electrical and Electronic Engineering Optical filter business Algorithm Mathematics |
| Zdroj: | Optics and Lasers in Engineering. 46:34-41 |
| ISSN: | 0143-8166 |
| Popis: | In this paper, we report a log-polar transform-based filter for in-plane rotation and scale-invariant target recognition. The log-polar transform is a known space-invariant image representation used in several image vision systems to eliminate the effects of scale and rotation in an image. In case of in-plane rotation invariance, peaks shift horizontally, while in case of scale invariance, peaks shift vertically. For full out-of-plane rotation-invariance (0–360°), log-polar transformed images are used to train the wavelet-modified maximum average correlation height (WaveMACH) filter. Correlation peak height and peak-to-sidelobe ratio have been calculated as metrics of goodness of the log-polar transform-based WaveMACH filter. This filter would reduce the memory requirement for filter storage in a practical system. Simulation results have been presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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