Local and Global Statistics-Based ExplicitActiveContour for Weld Defect ExtractioninRadiographic Inspection

74 Notre travail de recherche avait pour but essentiel d’acquérir des compétences en simulation informatique, en particulier le docking moléculaire par AutoDock

With the advances in computer science and artificial intelligence techniques, the opportunity to develop computer aided technique for radiographic inspection

In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2D histogram and locally adaptive approach for

With the advances in computer science and artificial intelligence techniques, the opportunity to develop computer aided technique for radiographic inspection in Non Destructive

The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece- wise

Weld defect features are computed from the segmentation result (final binary level set).. We have computed several features; they are ranked in two categories: Geometric features

Implementation is performed by a deterministic iterative algorithm that drives the model quickly to the boundaries, by limiting the investigation to the pixels laying in the

Implementation is performed by a deterministic iterative algorithm that drives the model quickly to the boundaries, by limiting the investigation to the pixels