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首页> 外文期刊>Computers & mathematics with applications >Automatic prior shape selection for image edge detection with modified Mumford-Shah model
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Automatic prior shape selection for image edge detection with modified Mumford-Shah model

机译:使用改进的Mumford-Shah模型进行图像边缘检测的自动先验形状选择

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摘要

Edge detection plays an important role in the field of image processing. In this paper, we propose a novel variational model to automatically and adaptively detect one or more prior shapes from the given dictionary to guide the edge detection process. In that way, we can effectively detect the shapes of interest from the test image. Moreover, an efficient algorithm based on the Alternating Direction Method of Multipliers (ADMM) is proposed to solve this model with guaranteed convergence. A variety of numerical experiments show that the proposed method has achieved ideal performance for edge detection in images with missing information, various types of noise and complicated background, and even multiple objects. (C) 2019 Elsevier Ltd. All rights reserved.
机译:边缘检测在图像处理领域中起着重要作用。在本文中,我们提出了一种新颖的变分模型,可以自动并自适应地从给定的字典中检测一个或多个现有形状,以指导边缘检测过程。这样,我们可以有效地从测试图像中检测出感兴趣的形状。此外,提出了一种基于乘数交替方向法(ADMM)的高效算法,以保证收敛性地求解该模型。多种数值实验表明,该方法在信息丢失,各种噪声,复杂背景甚至多个物体的图像边缘检测中均取得了理想的性能。 (C)2019 Elsevier Ltd.保留所有权利。

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