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A Hybride Active Contour Model Driven by Global and Local Image Information

机译:由全局和本地图像信息驱动的混合活动轮廓模型

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摘要

In this paper, a novel active contour model based on hybrid image fitting energy which utilizes both global and local image information is proposed. Two fitting images are constructed to approximate the original image and the square of the original image. Both global and local image information are incorporated into these two fitting images. Based on these two fitting images, a hybrid image fitting energy, which is then minimized in a variational level set framework to guide the evolving contours to the desired boundaries. The proposed approach is validated by experiments on both synthetic and real images. The experiments demonstrate that the proposed model is more efficient and robust for segmenting different kinds of images compared with several typical active contour models.
机译:本文提出了一种基于混合图像拟合能量的新型活性轮廓模型,其利用全局和局部图像信息。构造两个拟合图像以近似原始图像和原始图像的平方。全局和本地图像信息都结合到这两个拟合图像中。基于这两个拟合图像,将混合图像配合能量最小化,然后在变形水平设定框架中最小化,以将演变的轮廓引导到所需边界。通过合成和真实图像的实验验证了所提出的方法。实验表明,与几种典型的有源轮廓模型相比,所提出的模型对分割不同种类的图像是更有效和稳健的。

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