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An Amalgam Approach to Detect Edges Using Ultrametric Contour Map in Natural Scene Images

机译:一种在自然场景图像中使用超轮廓线图检测边缘的汞合金方法

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Detection of straight lines in digital images is a reappearing problem in image processing and computer vision tasks. Typically the edges or lines in an image are considered as a very influential component which carries crucial information about the whole image. This important component can be extracted by employing various edge detection methods. Generally, the lines are formed by boundary pixels which connect two isolated regions, hence it easy to detect such edges between the regions. Still, it has some obstacles to detect weak edge pixels that form a continuous straight line in natural scenes. Here in this paper, we proposed a method to detect straight lines in such natural scene images which contain “Roads”, “Bridge”, “Pavement”, and similar type of archaeological and natural structures. Such structures in photographs start from the bottom of the frame and move towards some region, object or meet at a vanishing point. The proposed method has been tested on our own dataset of natural scene images and we have seen that our proposed method to detect lines for some specific images performs much better upon current state-of-the-art in the line detection techniques.
机译:在图像处理和计算机视觉任务中,数字图像中直线的检测是一个重新出现的问题。通常,图像中的边缘或线条被认为是非常有影响力的组件,它承载有关整个图像的关键信息。可以通过采用各种边缘检测方法来提取此重要成分。通常,线由连接两个隔离区域的边界像素形成,因此容易检测区域之间的这种边缘。尽管如此,检测在自然场景中形成连续直线的弱边缘像素还是有一些障碍。在本文中,我们提出了一种在包含“道路”,“桥梁”,“路面”以及类似类型的考古和自然结构的自然场景图像中检测直线的方法。照片中的此类结构从相框的底部开始,并朝某个区域,物体或消失点汇合。该提议的方法已经在我们自己的自然场景图像数据集上进行了测试,并且我们已经看到,提出的用于检测某些特定图像的线条的方法在行检测技术的当前最新水平上表现更好。

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