Functional Asplund Metrics for Pattern Matching, Robust to Variable Lighting Conditions

Guillaume Noyel; Michel Jourlin

doi:10.5566/ias.2292

Authors

Guillaume Noyel University of Strathclyde, Department of Mathematics and Statistics International Prevention Research Institute https://orcid.org/0000-0002-7374-548X
Michel Jourlin Université Jean Monnet, Laboratoire Hubert Curien International Prevention Research Institute https://orcid.org/0000-0002-2076-3465

DOI:

https://doi.org/10.5566/ias.2292

Keywords:

Asplund metrics, Double-sided probing, Logarithmic Image Processing, Map of Asplund distances, Mathematical Morphology, Pattern matching, Robustness to lighting variation

Abstract

In this paper, we propose a complete framework to process images captured under uncontrolled lighting and especially under low lighting. By taking advantage of the Logarithmic Image Processing (LIP) context, we study two novel functional metrics: i) the LIP-multiplicative Asplund metric which is robust to object absorption variations and ii) the LIP-additive Asplund metric which is robust to variations of source intensity or camera exposure-time. We introduce robust to noise versions of these metrics. We demonstrate that the maps of their corresponding distances between an image and a reference template are linked to Mathematical Morphology. This facilitates their implementation. We assess them in various situations with different lightings and movement. Results show that those maps of distances are robust to lighting variations. Importantly, they are efficient to detect patterns in low-contrast images with a template acquired under a different lighting.

Author Biography

Guillaume Noyel, University of Strathclyde, Department of Mathematics and Statistics International Prevention Research Institute

University of Strathclyde, Glasgow, Scotland, United Kingdom, Visiting Researcher
International Prevention Research Institute, Lyon, France Research Director

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