Research and development of image homology identification technology based on fine registration

Zhiqing Bai; James A. Esquivel

doi:10.1117/12.3035451

19 July 2024 Research and development of image homology identification technology based on fine registration

Zhiqing Bai, James A. Esquivel

Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132131U (2024) https://doi.org/10.1117/12.3035451
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China

Abstract

The function of recording and reproducing facts according to statistics is widely used. However, the appearance of image editing software makes it easy to tamper with image information, which reduces its credibility and authenticity. Therefore, judging and restoring the originality, authenticity, and integrity of digital images has become an urgent problem to be solved. To address these issues, we propose a corresponding image recognition technology based on fine registration. We measure the system of image matching and automatic correction for users in different shooting angles, image sizes, image acquisition devices, image rotation differences, and different lighting conditions. This technology aims to eliminate noise pollution in the process of image transmission and establish testing standards for images. Through the deep learning process, we have achieved a high-precision image homology recognition method that possesses the characteristics of good robustness, fast response speed, and strong practicability.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhiqing Bai and James A. Esquivel "Research and development of image homology identification technology based on fine registration", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132131U (19 July 2024); https://doi.org/10.1117/12.3035451

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KEYWORDS

Image registration

Digital imaging

Deep learning

Education and training

Image processing

Image restoration

Image segmentation

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