Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/48813
Título: | Digital right management control for joint ownership of digital images using biometric features | Autores/as: | Singh, Anushikha Dutta, Malay Kishore Travieso, Carlos M. Soni, K. M. |
Clasificación UNESCO: | 220990 Tratamiento digital. Imágenes | Palabras clave: | Multiple biometric features Iris Pattern Recognition Robustness Signal Processing Attacks Digital watermarking, et al. |
Fecha de publicación: | 2014 | Publicación seriada: | 2014 International Conference on Signal Processing and Integrated Networks, SPIN 2014 | Conferencia: | 1st International Conference on Signal Processing and Integrated Networks, SPIN 2014 | Resumen: | This paper proposes a method to establish joint ownership of digital images by embedding imperceptible digital pattern in the image. This digital pattern is generated from biometric features of more than one subject in a strategic matter so that the identification of individual subject can be done and the multiple ownership of the digital images can be established. This digital pattern was embedded and extracted from the image and the experiments were also carried out when the image was subjected to signal processing attacks. Coefficients of mid frequency band discrete cosine transform was used for embedding as these coefficients do not adversely affect the perceptual transparency and is also significantly robust to normal signal processing attacks. Experimental results indicate that the insertion of this digital pattern does not change the perceptual properties of the image and the pattern survives signal processing attacks which can be extracted for unique identification. © 2014 IEEE. | URI: | http://hdl.handle.net/10553/48813 | ISBN: | 9781479928668 | Fuente: | 2014 International Conference on Signal Processing and Integrated Networks, SPIN 2014 (6776941), p. 164-167 |
Colección: | Actas de congresos |
Citas SCOPUSTM
3
actualizado el 15-dic-2024
Visitas
25
actualizado el 02-dic-2023
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.