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Adaptive Thresholding for Edge Detection in Gray Scale Images

机译:灰度图像边缘检测的自适应阈值

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Digital image processing is a subset of the electronic domain, wherein the image is converted to an array of small integers, called pixels, representing a physical quantity. Edges characterize boundaries and edge detection is one of the most difficult tasks in image processing hence it is a problem of fundamental importance in image processing. The problem of edge detection although it is fundamental and is existing since years but it is still an area where there is still scope of research. It has been found that the previous used algorithms or methods were not able to produce ideal or optimized results. This paper presents an edge detection method applicable to gray level images in which an objective function is used to extract edge points as well as their directions. Adaptive thresholding technique is used there after to suppress non maximum points and to highlight edge points.
机译:数字图像处理是电子领域的子集,其中,图像被转换为​​代表物理量的称为像素的小整数数组。边缘代表边界,边缘检测是图像处理中最困难的任务之一,因此,这是图像处理中至关重要的问题。边缘检测的问题虽然是根本的,并且已经存在多年,但是它仍然是一个仍有研究范围的领域。已经发现,先前使用的算法或方法不能产生理想或优化的结果。本文提出了一种适用于灰度图像的边缘检测方法,其中使用目标函数提取边缘点及其方向。之后,使用自适应阈值技术来抑制非最大点并突出显示边缘点。

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