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A threshold strategy for edge tracking

机译:边缘跟踪的阈值策略

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In this paper, we address a threshold strategy based on fuzzy sets theory, which can be used to guide an edge tracking execution. First, we briefly introduce the principle of edge tracking technique. A set of edge models is proposed. The cost functions are defined not only according to the change of local gradient magnitude but also to the change of local gradient directions. A set of thresholds is defined in terms of the histogram of edge enhanced images to determine the start and the end of edge tracking. So that, no matter how much the intensity levels of images vary, the algorithm will always gain the best edge extraction. The fuzzy sets concept is used to combine the human linguistic language into the operation of the determination of edge contrast to the background. A more acceptable interface is established according to the human visual perception. The new algorithm has been tested on several real world images and the experimental results are given.
机译:在本文中,我们基于模糊集理论来解决基于模糊集合的阈值策略,其可用于引导边缘跟踪执行。首先,我们简要介绍了边缘跟踪技术的原理。提出了一组边缘模型。成本函数不仅根据局部梯度幅度的变化而定义,而且还定义了局部梯度方向的变化。在边缘增强图像的直方图方面定义了一组阈值,以确定边缘跟踪的开始和结束。因此,无论图像的强度水平如何变化,算法都会始终获得最佳的边缘提取。模糊集合概念用于将人类语言语言与背景结合到边缘对比度的操作。根据人类视觉感知建立更可接受的界面。新算法已经在几个现实世界图像上进行了测试,并给出了实验结果。

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