Extraction of weld defects dimension from radiographic images using the level set segmentation without re-initialization

Halimi, M.; Ramou, N.

doi:10.1134/s1061830913070036

Cited by 6 publications

(1 citation statement)

References 4 publications

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“…An automated algorithm used for segmenting the phases present in the scanning electron microscopic images of dual phase steel [7][8][9]. A level set segmentation model was proposed to analysis the images of particle to overcome the drawback of sensitivity to weak boundaries and curve's initial position [10]. In this way, we thus propose a different approach for image segmentation which is based on using a multiphase level set Mumford and Shah to segment the phases present in the scanning microscopic images of metallographic samples.…”

Section: Introductionmentioning

confidence: 99%

Automatic image segmentation for material microstructure characterization by optical microscopy

Ramou

Chetih

Boutiche

et al. 2020

IJCAI

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This work shows the microstructure characterization utility for the analysis of material properties. To achieve this purpose, digital image segmentation is used on microscopic images of materials to extract the number of phases and their proportion present in the material to obtain a quantitative description of material properties and to better control product quality. In this way, we present here an automated method for segmenting the phases present in microscopic scanning images of metallographic samples using a multiphase level set with Mumford Shah formulation. Experience shows that the proposed model successfully detects phase regions for a variety of real micrographic images Povzetek: Predstavljena je metoda za segmentiranje slik, pridobljenih z optičnim mikroskopom, za ugotavljanje lastnosti materiala..

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Section: Introductionmentioning

confidence: 99%