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Edge detection methods

机译:边缘检测方法

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Edge detection is a type of image segmentation techniques which determines the presence of an edge or line in an image and outlines them in an appropriate way. The main purpose of edge detection is to simplify the image data in order to minimize the amount of data to be processed. Generally, an edge is defined as the boundary pixels that connect two separate regions with changing image amplitude attributes such as different constant luminance and tristimulus values in an image. In this paper, we present methods for edge segmentation of images; we used five techniques for this category; Sobel operator technique, Prewitt technique, Laplacian technique, Canny technique, Roberts technique, and they are compared with one another so as to choose the best technique for edge detection segment image. These techniques applied on one image to choose base guesses for segmentation or edge detection image. In this paper an attempt is made to study the performance of most commonly used edge detection techniques for image segmentation and also the comparison of these techniques is carried out with an experiment by using MATLAB software. We will use the edges to find congruence between objects.
机译:边缘检测是一种图像分割技术,可确定图像中边缘或线条的存在并以适当的方式勾勒出它们的轮廓。边缘检测的主要目的是简化图像数据,以最小化要处理的数据量。通常,将边缘定义为边界像素,该边界像素连接两个具有变化的图像幅度属性(例如,图像中的恒定亮度和三刺激值)的独立区域。在本文中,我们提出了图像的边缘分割方法。我们为此类别使用了五种技术;将Sobel算子技术,Prewitt技术,Laplacian技术,Canny技术,Roberts技术相互比较,从而为边缘检测段图像选择最佳技术。这些技术应用于一张图像,以选择用于分割或边缘检测图像的基本猜测。本文尝试研究最常用的边缘检测技术进行图像分割的性能,并使用MATLAB软件通过实验对这些技术进行了比较。我们将使用边缘查找对象之间的一致性。

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