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Physics-Based Image Segmentation Using First Order Statistical Properties and Genetic Algorithm for Inductive Thermography Imaging
2018
IEEE Transactions on Image Processing
Thermographic inspection has been widely applied to Non-Destructive Testing and Evaluation (NDT&E) with capabilities of rapid, contactless and large surface area detection. Image segmentation is considered essential for identifying and sizing defects. To attain a high level performance, specific physics-based models that describe defects generation and enable the precise extraction of target region are of crucial importance. In this paper, an effective genetic first order statistical image
doi:10.1109/tip.2017.2783627
pmid:29432098
fatcat:5worcrfkhzgnzjvauha6tlt6tq