Abstract
The registration of printed images and the original image before printing is the key step of high precision quality detection of printed image. In the printing process and the process of collecting printed images, rigid deformation, elastic deformation and brightness difference between the original image and the printed image are inevitably caused to the printed image. In order to improve the registration accuracy of printed images and deal with various deformations and color differences that may occur during the printing process, this paper proposes an innovative algorithm that combines feature registration and deformation optimization. The algorithm first uses the SIFT feature extraction algorithm to achieve global registration, and then combines the Active Demons deformation estimation algorithm to optimize the local deformation to correct the rigid and elastic deformation of the printed image. However, the deformation estimation algorithm is limited by the premise of the same brightness. Therefore, this paper performs superpixel segmentation on the original image before printing, and then introduces a nonlinear brightness compensation mechanism, thus overcoming the brightness constraint of the deformation estimation algorithm. In order to improve the registration efficiency, a reduction factor is adaptively introduced in the global registration stage, and the local deformation optimization registration stage cancels the iteration by designing the value of the normalization factor. The experimental results show that compared with SIFT, Active Demons and SIFT-ActiveDemons algorithms, the innovative fusion registration algorithm in this paper has the highest registration accuracy and can effectively correct the elastic deformation of printed images.
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Chen, Y., Zhang, L., Zhan, H. et al. Registration algorithm for printed images incorporating feature registration and deformation optimization. SIViP 19, 176 (2025). https://doi.org/10.1007/s11760-024-03794-x
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DOI: https://doi.org/10.1007/s11760-024-03794-x