Abstract
In this paper we present a new methodology for edge detection in digital images. The first originality of the proposed method is to consider image content as a parametric surface. Then, an original parametric local model of this surface representing image content is proposed. The few parameters involved in the proposed model are shown to be very sensitive to discontinuities in surface which correspond to edges in image content. This naturally leads to the design of an efficient edge detector. Moreover, a thorough analysis of the proposed model also allows us to explain how these parameters can be used to obtain edge descriptors such as orientations and curvatures. In practice, the proposed methodology offers two main advantages. First, it has high customization possibilities in order to be adjusted to a wide range of different problems, from coarse to fine scale edge detection. Second, it is very robust to blurring process and additive noise. Numerical results are presented to emphasis these properties and to confirm efficiency of the proposed method through a comparative study with other edge detectors.
Abstract (translated)
本文提出了一种新的数字图像边缘检测方法。该方法的第一个创新点是将图像内容作为参数曲面。在此基础上，提出了一种表示图像内容的曲面参数化局部模型。模型中涉及的几个参数对图像内容中边缘对应的表面不连续非常敏感。这自然导致了一个有效的边缘探测器的设计。此外，对所提出的模型进行了深入的分析，也使我们能够解释如何使用这些参数来获得诸如方向和曲率等边缘描述符。
URL
https://arxiv.org/abs/1904.10235
