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Publikacje Pracowników Politechniki Lubelskiej

MNiSW
100
Lista 2024
Status:
Autorzy: Kozieł Grzegorz, Malomuzh Liudmyla
Dyscypliny:
Aby zobaczyć szczegóły należy się zalogować.
Rok wydania: 2024
Wersja dokumentu: Drukowana | Elektroniczna
Język: angielski
Numer czasopisma: 8
Wolumen/Tom: 18
Strony: 351 - 365
Impact Factor: 1,0
Scopus® Cytowania: 0
Bazy: Scopus
Efekt badań statutowych NIE
Materiał konferencyjny: NIE
Publikacja OA: TAK
Licencja:
Sposób udostępnienia: Otwarte czasopismo
Wersja tekstu: Ostateczna wersja opublikowana
Czas opublikowania: W momencie opublikowania
Data opublikowania w OA: 1 listopada 2024
Abstrakty: angielski
With the development of new technologies, 3D models are becoming increasingly important. They are used to design new models, document cultural heritage and scan valuable artefacts or evidence. They are also used in medicine. For these reasons, they are vulnerable to forgery. Protection against forgery done by encrypting the model or signing it digitally may restrict access to the data or require additional files to store the signatures. A good way to confirm the originality of 3D models is fingerprinting. This technique involves attaching a fragile water- mark directly to the watermarked data. In the paper, we propose a new fingerprinting method for 3D models. The method hides the fingerprint in the least significant digits of the coordinates of the selected vertices. The fingerprint is created by calculating the hash-based message authentication code (HMAC) from the model textures and all vertex coordinates except the digits intended to attach the fingerprint. These digits are processed using discrete wavelet transform (DWT). The HMAC is attached to the selected DWT coefficients. The inverse discrete wavelet transform is then performed to obtain the new values of the modified digits. The digits are put back into the 3D model coordinates and the model is reassembled. Verification of the model originality is done according to the used steganographic key and consists of comparing the HMAC value extracted from the fingerprinted model with the HMAC value calculated from it. The same values of both HMAC results indicate that the model has not been modified. The proposed method allows efficient model fingerprinting and detection of changes made to any part of the model. The included fingerprints are transparent – the peak signal-to-noise ratio (PSNR) of a fingerprinted model can reach 150dB and its structural similarity can be over 99.8%. This paper presents a novel, computation- ally efficient fragile watermarking scheme that is capable of detecting the smallest changes in any part of a 3D model. The presented solution can be used to confirm the originality of 3D models. In particular, it will work well for fingerprinting large models such as 3D scans of architectural objects.