Logarithmic Mathematical Morphology: A New Framework Adaptive to Illumination Changes

  • Guillaume NoyelEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11401)


A new set of mathematical morphology (MM) operators adaptive to illumination changes caused by variation of exposure time or light intensity is defined thanks to the Logarithmic Image Processing (LIP) model. This model based on the physics of acquisition is consistent with human vision. The fundamental operators, the logarithmic-dilation and the logarithmic-erosion, are defined with the LIP-addition of a structuring function. The combination of these two adjunct operators gives morphological filters, namely the logarithmic-opening and closing, useful for pattern recognition. The mathematical relation existing between “classical” dilation and erosion and their logarithmic-versions is established facilitating their implementation. Results on simulated and real images show that logarithmic-MM is more efficient on low-contrasted information than “classical” MM.


Mathematical morphology Contrast variations Illumination changes Logarithmic Image Processing Pattern recognition 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of Strathclyde Institute of Global Public HealthEcullyFrance
  2. 2.International Prevention Research Institute, iPRILyonFrance

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