Edge detection is a fundamental problem in image processing and computer vision. The purpose of edge detection is to identify points in digital images where brightness changes significantly.Significant changes in image properties usually reflect important events and changes in the properties. These include (i) discontinuities in depth, (ii) discontinuities in surface orientation, (iii) changes in material properties, and (iv) changes in scene illumination. Edge detection is a research area in image processing and computer vision, especially feature detection.

Edge DetectionCategories

Image edge detection greatly reduces the amount of data and removes irrelevant information, retaining the important structural properties of the image. There are many methods for edge detection.Most of them can be divided into two categories: those based on search and those based on zero-crossing.

• Search-based methods detect boundaries by finding the maximum and minimum values in the first-order derivative of the image, usually locating the boundary in the direction of the largest gradient.
• The zero-crossing based method finds the boundary by finding the zero-crossing of the second-order derivative of the image, usually the zero-crossing point of the Laplacian or the zero-crossing point of the nonlinear difference representation.

References

【1】https://zh.wikipedia.org/wiki/%E8%BE%B9%E7%BC%98%E6%A3%80%E6%B5%8B

【2】https://encord.com/glossary/edge-detection-definition/