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Fuzzy logic and fuzzy set theory based edge detection algorithm

机译:基于模糊逻辑和模糊集理论的边缘检测算法

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In this paper we will show a way how to detect edges in digital images. Edge detection is a fundamental part of many algorithms, both in image processing and in video processing. Therefore it is important that the algorithm is efficient and, if possible, fast to carry out. The fuzzy set theory based approach on edge detection is good for use when we need to make some kind of image segmentation, or when there is a need for edge classification (primary, secondary, ...). One example that motivated us is region labeling; this is a process by which the digital image is divided in units and each unit is given a unique label (sky, house, grass, …, etc.). To accomplish that, we need to have an intelligent system that will precisely determine the edges of the region. In this paper we will describe tools from image processing and fuzzy logic that we use for edge detection as well as the proposed algorithm.
机译:在本文中,我们将展示一种如何检测数字图像边缘的方法。边缘检测是图像处理和视频处理中许多算法的基本部分。因此,重要的是该算法必须高效且尽可能快地执行。当需要进行某种图像分割时,或者需要进行边缘分类(主要,次要,...)时,基于模糊集理论的边缘检测方法非常适合使用。激励我们的一个例子是区域标签。在此过程中,将数字图像划分为多个单位,并为每个单位分配一个唯一的标签(天空,房屋,草地等)。为此,我们需要一个智能系统来精确确定区域的边缘。在本文中,我们将描述用于边缘检测的图像处理和模糊逻辑工具以及所提出的算法。

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