REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS

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 homog...

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Main Authors: Guillaume Noyel, Michel Jourlin
Format: Article
Language:English
Published: Slovenian Society for Stereology and Quantitative Image Analysis 2019-04-01
Series:Image Analysis and Stereology
Subjects:
Online Access:https://www.ias-iss.org/ojs/IAS/article/view/2038
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spelling doaj-a58f7f8512294daa96f2e0f8dd0849522020-11-24T21:47:24ZengSlovenian Society for Stereology and Quantitative Image AnalysisImage Analysis and Stereology1580-31391854-51652019-04-01381435210.5566/ias.20381012REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMSGuillaume Noyel0Michel Jourlin1International Prevention Research Institute, Lyon, France University of Strathclyde Institute of Global Public Health, Dardilly - Lyon Ouest, FranceLaboratoire Hubert Curien, UMR CNRS 5516, Université Jean Monnet, Saint-Etienne, France International Prevention Research Institute, Lyon, FranceIn 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.https://www.ias-iss.org/ojs/IAS/article/view/2038Homogeneity of an image regionImage segmentationLogarithmic Image ProcessingRegion GrowingRobustness to lighting changes
collection DOAJ
language English
format Article
sources DOAJ
author Guillaume Noyel
Michel Jourlin
spellingShingle Guillaume Noyel
Michel Jourlin
REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS
Image Analysis and Stereology
Homogeneity of an image region
Image segmentation
Logarithmic Image Processing
Region Growing
Robustness to lighting changes
author_facet Guillaume Noyel
Michel Jourlin
author_sort Guillaume Noyel
title REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS
title_short REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS
title_full REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS
title_fullStr REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS
title_full_unstemmed REGION HOMOGENEITY IN THE LOGARITHMIC IMAGE PROCESSING FRAMEWORK: APPLICATION TO REGION GROWING ALGORITHMS
title_sort region homogeneity in the logarithmic image processing framework: application to region growing algorithms
publisher Slovenian Society for Stereology and Quantitative Image Analysis
series Image Analysis and Stereology
issn 1580-3139
1854-5165
publishDate 2019-04-01
description 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.
topic Homogeneity of an image region
Image segmentation
Logarithmic Image Processing
Region Growing
Robustness to lighting changes
url https://www.ias-iss.org/ojs/IAS/article/view/2038
work_keys_str_mv AT guillaumenoyel regionhomogeneityinthelogarithmicimageprocessingframeworkapplicationtoregiongrowingalgorithms
AT micheljourlin regionhomogeneityinthelogarithmicimageprocessingframeworkapplicationtoregiongrowingalgorithms
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