Wen Tingting, Fan Sijie
Rao Zongyi Cultural Research Institute of Shenzhen University, Shenzhen 518000, China.
School of Fine Arts and Design, Guangzhou University, Guangzhou 510000, China.
Comput Intell Neurosci. 2022 Apr 25;2022:5799198. doi: 10.1155/2022/5799198. eCollection 2022.
In order to improve the analysis effect of traditional arts and crafts, this paper analyzes traditional arts and crafts combined with digital technology, builds an intelligent analysis system to improve the digital processing effect of traditional arts and crafts, and takes the Guangdong-Hong Kong-Macao Greater Bay Area as an example to verify the system effect. In order to improve the accuracy of subsequent image alignment and defect detection, this paper compares the effects of the pixel-level edge detection algorithm and the subpixel-level edge detection algorithm and finally selects the subpixel-based edge detection algorithm to extract the edge of the image. In addition, this paper compares the traditional defect detection algorithm through research and experiment and proposes an improved image phase difference method according to the actual situation. The experimental research shows that the traditional arts and crafts intelligent analysis system based on digital technology proposed in this paper has a very good effect. At the same time, with the support of this system, the intelligent analysis of traditional arts and crafts in the Guangdong-Hong Kong-Macao Greater Bay Area can be carried out efficiently.
为提高传统工艺美术的分析效果，本文将传统工艺美术与数字技术相结合进行分析，构建智能分析系统以提升传统工艺美术的数字处理效果，并以粤港澳大湾区为例验证系统效果。为提高后续图像配准和缺陷检测的精度，本文对比了像素级边缘检测算法和亚像素级边缘检测算法的效果，最终选用基于亚像素的边缘检测算法来提取图像边缘。此外，本文通过研究和实验对比了传统缺陷检测算法，并根据实际情况提出了改进的图像相位差法。实验研究表明，本文提出的基于数字技术的传统工艺美术智能分析系统具有很好的效果。同时，在该系统的支持下，可高效开展粤港澳大湾区传统工艺美术的智能分析。
