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

• Published in: Image analysis & stereology Vol. 39; no. 2; pp. 53 - 71
• Main Authors: Noyel, Guillaume, Jourlin, Michel
• Format: Journal Article
• Language: English
• Published: International Society for Stereology 01.01.2020; Slovenian Society for Stereology and Quantitative Image Analysis
• Subjects: asplund metrics; Computer Science; Computer Vision and Pattern Recognition; double-sided probing; Engineering Sciences; Functional Analysis; logarithmic image processing; map of asplund distances; mathematical morphology; Mathematics; Numerical Analysis; pattern matching; robustness to lighting variation; Signal and Image processing; Grayscale pattern matching; Double-sided probing; Robustness to lighting variations; Map of Asplund distances; Asplund metrics; Pattern matching; Mathematical Morphology; Logarithmic Image Processing
• ISSN: 1580-3139; 1854-5165
• DOI: 10.5566/ias.2292

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.