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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2019-04-01
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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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1725897220480303104 |