Abstract
With the development of mathematics and artificial intelligence, various types of edge algorithms are emerging, and theories such as neural networks are applied to image edge detection. However, due to the contradiction between detection accuracy, edge positioning accuracy and anti-noise, there are still some inconsistencies in edge detection. How to achieve accurate positioning and extraction of image edges has become an important issue that people must face. In this paper, the principle method of image edge extraction is deeply studied and explored. The main work is reflected in the following aspects:First, the meaning and prospect of image edge extraction are analyzed and discussed. Then introduce the basic theory of graphics extraction, enumerate and explain the current various extraction algorithms, focus on the canny algorithm and the robot algorithm, and obtain their extracted images through experimental simulation, from image extraction effect, peak signal-to-noise ratio and time overhead. Several parties have made comparisons. Secondly, the MATLAB experimental simulation platform is introduced, and the user interface design and development is carried out on this platform, and the code is given for some functions. Finally, this paper gives a comprehensive summary of the work of the thesis, and looks forward to the further research on image edge extraction.
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