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Research on Thangka Image Edge Detection Based on Differential Operator

机译:基于微分算子的唐卡图像边缘检测研究

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Edge detection is not only the early work of image segmentation, but also the basis of image understanding, differential operator is a simple technique for edge detection and is typically accomplished by calculating gradients of horizontal and vertical gray values. However, there are many curves that two-direction operator can detect that is not so clear in Thangka image. In this paper, the edge detection effects of several common differential operators on Thangka image are compared. On the basis, a new algorithm for Thangka image detection is proposed. Fist the image is grayed. The the grays image is contrast reduced. At last edge detection of image is carried out by using four-direction Sobel operator.
机译:边缘检测不仅是图像分割的早期工作,而且还是图像理解的基础,差分算子是边缘检测的一种简单技术,通常通过计算水平和垂直灰度值的梯度来完成。但是,在唐卡图像中,很多方向的双向操作者可以检测到的曲线并不十分清晰。在本文中,比较了几种常见的微分算子对唐卡图像的边缘检测效果。在此基础上,提出了一种新的唐卡图像检测算法。拳头图像变灰。灰度图像对比度降低。最后,使用四向Sobel算子对图像进行边缘检测。

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