Image segmentation-based robust feature extraction for color image watermarking

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

[1]  C. Schmid,et al.  Indexing based on scale invariant interest points , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[2]  Cordelia Schmid,et al.  A sparse texture representation using local affine regions , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[4]  Michel Barlaud,et al.  Compensation of geometrical deformations for watermark extraction in digital cinema application , 2001, IS&T/SPIE Electronic Imaging.

[5]  Gregory W. Wornell,et al.  Preprocessed and postprocessed quantization index modulation methods for digital watermarking , 2000, Electronic Imaging.

[6]  Gregory W. Wornell,et al.  Provably robust digital watermarking , 1999, Optics East.

[7]  D. A. Karras,et al.  Color image watermarking via Quaternion Radial Tchebichef Moments , 2013, 2013 IEEE International Conference on Imaging Systems and Techniques (IST).

[8]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[9]  Pascal Fua,et al.  SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[11]  Gregory W. Wornell,et al.  Quantization index modulation: A class of provably good methods for digital watermarking and information embedding , 2001, IEEE Trans. Inf. Theory.

[12]  Fernando Pérez-González,et al.  The effect of the random jitter attack on the bit error rate performance of spatial domain image watermarking , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[13]  Xiangyang Wang,et al.  A robust blind color image watermarking in quaternion Fourier transform domain , 2013, J. Syst. Softw..

[14]  Cordelia Schmid,et al.  A Performance Evaluation of Local Descriptors , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .