Homogeneity of a region in the logarithmic image processing framework: application to region growing algorithms

Michel Jourlin (1, 2) , Guillaume Noyel (2, 3, 4)

1 LHC - Laboratoire Hubert Curien
2 IPRI - International Prevention Research Institute
3 SIGPH@iPRI - University of Strathclyde Institute of Global Public Health
4 University of Strathclyde [Glasgow]

The current paper deals with the role played by Logarithmic Image Processing (LIP) operators for evaluating the homogeneity of a region. Two new criteria of heterogeneity are introduced, one based on the LIP addition and the other based on the LIP scalar multiplication. Such tools are able to manage Region Growing algorithms following the Revol's technique: starting from an initial seed, they consist of applying specific dilations to the growing region while its inhomogeneity level does not exceed a certain level. The new approaches we introduce are significantly improving Revol's existing technique by making it robust to contrast variations in images. Such a property strongly reduces the chaining effect arising in region growing processes.

Mots clés: chaining effect; region growing; homogeneity; heterogeneity criterion; segmentation; LIP; Logarithmic Image Processing; low-contrasted images

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Analyse numérique [math.NA]; Traitement du signal et de l'image [eess.SP]

Michel Jourlin, Guillaume Noyel. Homogeneity of a region in the logarithmic image processing framework: application to region growing algorithms. Physics and Mechanics of Random Structures: from Morphology to Material Properties, Jun 2018, Ile d'Oléron, France. pp.5-7. ⟨hal-01822522⟩