On the Reliability of Computing Wigner Texture Features

Authors:
Svetlana Barsky;Maria Petrou
Affiliations:
School of Electronic Engineering, Information Technology and Mathematics, University of Surrey, Guildford, GU2 7XH, UK;School of Electronic Engineering, Information Technology and Mathematics, University of Surrey, Guildford, GU2 7XH, UK
Venue:
Journal of Mathematical Imaging and Vision
Year:
2002

Citing 5
Cited 0

Computational vision

Computational vision
Texture crack detection

Machine Vision and Applications
Digital image processing

Digital image processing
Performance characteristics of vision algorithms

Machine Vision and Applications - Special issue on performance evaluation
Algorithmic modelling for performance evaluation

Machine Vision and Applications - Special issue on performance evaluation

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Abstract

In this work we analyse the robustness of the computation of pseudo-Wigner texture features using both analytic and statistical methods. It is shown that if the input error is normally distributed and the SNR of the input is not very low (i.e. if SNR ≥ 3), then the output error is also normally distributed with known mean and variance. The error distribution in some typical simple signals is considered. The effects of quantisation are also investigated.