Abstract
The paper is related to the verification of the usefulness of some metrics, typically used for image quality assessment and texture similarity evaluation, for no-reference quality assessment of 3D prints. The proposed approach is based on the assumption that a surface of high quality 3D print should be homogeneous and therefore some parts of it should be self-similar. Considering the local similarity of some fragments of 3D prints, some distortions can be detected which lower the overall quality of the 3D print. Since many image quality assessment methods, as well as texture similarity metrics, are based on the comparison of fragments of two images, a modification of such approach has been proposed which allows the no-reference evaluation without any information about the reference image or model.
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Okarma, K., Fastowicz, J., Tecław, M. (2016). Application of Structural Similarity Based Metrics for Quality Assessment of 3D Prints. In: Chmielewski, L., Datta, A., Kozera, R., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2016. Lecture Notes in Computer Science(), vol 9972. Springer, Cham. https://doi.org/10.1007/978-3-319-46418-3_22
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DOI: https://doi.org/10.1007/978-3-319-46418-3_22
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