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In this paper, we propose a complete framework to process images capturedunder uncontrolled lighting and especially under low lighting. By takingadvantage of the Logarithmic Image Processing (LIP) context, we study two novelfunctional metrics: i) the LIP-multiplicative Asplund metric which is robust toobject absorption variations and ii) the LIP-additive Asplund metric which isrobust to variations of source intensity or camera exposure-time. We introducerobust to noise versions of these metrics. We demonstrate that the maps oftheir corresponding distances between an image and a reference template arelinked to Mathematical Morphology. This facilitates their implementation. Weassess 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 witha template acquired under a different lighting.

Functional Asplund metrics for pattern matching, robust to variable lighting conditions