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<p>This research aims to create an image registration system specific to art design, employing an upgraded version of the Speeded-Up Robust Features algorithm, known as Gradient Speeded-Up Robust Features. Optimizing computational efficiency during the processing of images, particularly for real-time analysis in scenarios in art design, is its key purpose. In its proposed algorithm, traditional rectangular templates have been replaced with circular ones, and a significant drop in computational intensity and improvements in feature detection and matching capabilities have been seen. Experimental results reveal a 25% drop in computation time and a 15% boost in correct matching when contrasted with the traditional Speeded-Up Robust Features algorithm. In addition, its average processing time for processing an image has been reduced by 1.2&#xa0;s, and therefore, it is particularly ideal for use in scenarios such as artwork installations, multimedia, and augmented reality environments. This work puts into prominence the growing role of computational approaches in art design and raises demand for continued improvements in image processing technology. The theory proposed in this work forms a basis for combining technology with registrations in images in art design and promotes innovation in works of digital and interactive artwork. Overall, these findings present avenues for improvements in even sophisticated processing in picture processing systems utilized in scenarios in art design.</p>

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Design of information art image registration system based on SURF algorithm

  • 期刊论文

  • 发表日期：

    2025年4月28日

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  • Lei Cui

摘要

This research aims to create an image registration system specific to art design, employing an upgraded version of the Speeded-Up Robust Features algorithm, known as Gradient Speeded-Up Robust Features. Optimizing computational efficiency during the processing of images, particularly for real-time analysis in scenarios in art design, is its key purpose. In its proposed algorithm, traditional rectangular templates have been replaced with circular ones, and a significant drop in computational intensity and improvements in feature detection and matching capabilities have been seen. Experimental results reveal a 25% drop in computation time and a 15% boost in correct matching when contrasted with the traditional Speeded-Up Robust Features algorithm. In addition, its average processing time for processing an image has been reduced by 1.2 s, and therefore, it is particularly ideal for use in scenarios such as artwork installations, multimedia, and augmented reality environments. This work puts into prominence the growing role of computational approaches in art design and raises demand for continued improvements in image processing technology. The theory proposed in this work forms a basis for combining technology with registrations in images in art design and promotes innovation in works of digital and interactive artwork. Overall, these findings present avenues for improvements in even sophisticated processing in picture processing systems utilized in scenarios in art design.