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Image segmentation for defect detection based on level set active contour combined with saliency map

机译:基于级别设置的缺陷检测图像分割,主动轮廓与显着图相结合

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In this paper we propose a new image segmentation method to detect surface defects with small shapes in images characterized by low contrast level and affected by non-uniform illumination. The proposed segmentation method is based on level set active contour approach where a center-surround feature saliency map used to suppress the clutter background and highlighting the potential objects is incorporated in the level set active contour formulation. Experimental results on different industrial images like welding and steel demonstrate the robustness and the accuracy in defect segmentation comparing with others active contour models.
机译:在本文中,我们提出了一种新的图像分割方法,以检测具有低对比度水平的图像中具有小形状的表面缺陷并受不均匀照明的影响。所提出的分割方法基于水平集有源轮廓方法,其中用于抑制杂波背景并突出显示潜在对象的中心环绕特征胶质型在电平活动轮廓制构中结合在一起。焊接和钢等不同工业图像上的实验结果证明了与其他有源轮廓模型相比的缺陷分割中的鲁棒性和准确性。

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