Asplünd׳s metric defined in the Logarithmic Image Processing (LIP) framework: A new way to perform double-sided image probing for non-linear grayscale pattern matching
| Autor: | Bassam Abdallah, Joris Corvo, Enguerrand Couka, Josselin Breugnot, Michel Jourlin |
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| Rok vydání: | 2014 |
| Předmět: |
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Context (language use) Scalar multiplication Grayscale Artificial Intelligence Computer Science::Computer Vision and Pattern Recognition Signal Processing Metric (mathematics) Digital image processing Computer vision Computer Vision and Pattern Recognition Sensitivity (control systems) Artificial intelligence Pattern matching Noise (video) business Software Mathematics |
| Zdroj: | Pattern Recognition. 47:2908-2924 |
| ISSN: | 0031-3203 |
| Popis: | The present paper focuses on non-linear pattern matching based on the Logarithmic Image Processing (LIP) Model. Our contribution consists first of using the scalar multiplication defined in the LIP context to extend the little-known Asplund׳s metric to gray level images. Such a metric is explainable as a novel technique of double-sided image probing and presents the decisive advantage of being physically justified in the field of transmitted light acquisition. Moreover, thanks to the consistency of the LIP context with human vision, Asplund׳s metric is also applicable to images acquired in reflected light: in fact, plenty of image processing algorithms aim at extracting information as a human eye would do. Finally, the proposed approach is particularly efficient in the presence of lighting variations or lighting drift. In the paper, we also suggest a solution to overcome the main drawback of probing techniques, which resides in a high sensitivity to noise. Various examples are presented to highlight the efficiency of the method. |
| Databáze: | OpenAIRE |
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