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Region homogeneity in the Logarithmic Image Processing framework: application to region growing algorithms

Abstract : In order to create an image segmentation method robust to lighting changes, two novel homogeneity criteria of an image region were studied. Both were defined using the Logarithmic Image Processing (LIP) framework whose laws model lighting changes. The first criterion estimates the LIP-additive homogeneity and is based on the LIP-additive law. It is theoretically insensitive to lighting changes caused by variations of the camera exposure-time or source intensity. The second, the LIP-multiplicative homogeneity criterion, is based on the LIP-multiplicative law and is insensitive to changes due to variations of the object thickness or opacity. Each criterion is then applied in Revol and Jourlin's (1997) region growing method which is based on the homogeneity of an image region. The region growing method becomes therefore robust to the lighting changes specific to each criterion. Experiments on simulated and on real images presenting lighting variations prove the robustness of the criteria to those variations. Compared to a state-of the art method based on the image component-tree, ours is more robust. These results open the way to numerous applications where the lighting is uncontrolled or partially controlled.
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Contributor : Guillaume Noyel <>
Submitted on : Monday, April 15, 2019 - 1:03:36 PM
Last modification on : Tuesday, June 23, 2020 - 7:37:06 PM


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Guillaume Noyel, Michel Jourlin. Region homogeneity in the Logarithmic Image Processing framework: application to region growing algorithms. Image Analysis and Stereology, International Society for Stereology, 2019, 38 (1), pp.43-52. ⟨10.5566/ias.2038⟩. ⟨hal-02099867⟩



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