A new color space domain for digital watermarking in multimedia applications

Many studies have shown that color representation is very relevant in image processing and communications techniques. In this contribution, we propose a new color space, based on the "skin" component, in order to minimize the perceptual distortions introduced by digital watermarking. We have therefore defined a new color space, called YST, in which the brightness component is the same of YUV. Conversely, the S (skin) component has been obtained estimating the average values corresponding to a set of different colors of human faces. The criterion for this selection was to achieve a reasonable degree of generalization. The third component, T, is automatically identified by the Gram-Schmidt procedure in order to have an orthogonal color space. Analytical results are used to show the benefits obtained in digital watermarking by the new representation as well as in terms of peak signal-to-noise ratio and video quality metrics.

[1]  Sebastian Lang,et al.  Improving adaptive skin color segmentation by incorporating results from face detection , 2002, Proceedings. 11th IEEE International Workshop on Robot and Human Interactive Communication.

[2]  Jesús Malo,et al.  Video quality measures based on the standard spatial observer , 2002, Proceedings. International Conference on Image Processing.

[3]  Alessandro Neri,et al.  Blind quality assessment system for multimedia communications using tracing watermarking , 2003, IEEE Trans. Signal Process..

[4]  Nasir Ahmed,et al.  On a realization and related algorithm for adaptive prediction , 1980 .

[5]  Alice Caplier,et al.  New color transformation for lips segmentation , 2001, 2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564).

[6]  Stephen Wolf,et al.  Video Quality Measurement Techniques , 2002 .

[7]  Sotiris Pavlopoulos,et al.  A medical image watermarking scheme based on wavelet transform , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[8]  Xinping Huang,et al.  A recursive Gram-Schmidt orthonormalization procedure and its application to communications , 2001, 2001 IEEE Third Workshop on Signal Processing Advances in Wireless Communications (SPAWC'01). Workshop Proceedings (Cat. No.01EX471).

[9]  Minoru Fukumi,et al.  Detection of human faces in visual scenes , 2001, The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001.

[10]  J. Tasic,et al.  Colour spaces: perceptual, historical and applicational background , 2003, The IEEE Region 8 EUROCON 2003. Computer as a Tool..

[11]  Hongya Ge Iterative Gram-Schmidt orthonormalization for efficient parameter estimation , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[12]  Athanassios N. Skodras,et al.  Color image-adaptive watermarking , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

[13]  Giovani Gómez On selecting colour components for skin detection , 2002, Object recognition supported by user interaction for service robots.

[14]  Ton Kalker,et al.  Speed-change resistant audio fingerprinting using auto-correlation , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..