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Momentum based level set segmentation for complex phase change thermography sequence

机译:基于动量的水平集分割用于复杂相变热成像序列

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Level set methods are often used to solve the image segmentation problem. A new method based on momentum level set segmentation is applied to extract phase change line automatically from complex phase change thermography sequence. Firstly, effective phase change information is obtained by the inter-frame difference with the template image and the differential image. Then, in consideration of the relevance of inter-frame phase change line, we present a tracking algorithm of the phase change line by level set segmentation method based on momentum. This new method is derived from gradient descent algorithm. It avoids many unwanted local optima and poor convergence which common level set methods suffer. Moreover, this method greatly improves convergence rate in comparison with C-V model method. The experimental results show that the method is able to solve multi-phase change lines and topology changes problems effectively which can not be solved by existing methods, and can adapt to variant test models.
机译:水平集方法通常用于解决图像分割问题。应用基于动量水平集分割的新方法,从复杂的相变热成像序列中自动提取相变线。首先,通过与模板图像和差分图像的帧间差异获得有效的相变信息。然后,考虑到帧间相变线的相关性,提出了一种基于动量的水平集分割方法对相变线进行跟踪的算法。这种新方法是从梯度下降算法中派生出来的。它避免了常见的水平集方法遭受的许多不必要的局部最优和收敛性差的问题。此外,与C-V模型方法相比,该方法大大提高了收敛速度。实验结果表明,该方法能够有效解决多相变线和拓扑变化问题,是现有方法无法解决的,并且能够适应变型测试模型。

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