LBP and DWT Based Fragile Watermarking for Image Authentication
2
조회
0
다운로드
3
인용
0
참고문헌
키워드
초록
The discrete wavelet transform (DWT) has good multi-resolution decomposition characteristic and its lowfrequency component contains the basic information of an image. Based on this, a fragile watermarking usingthe local binary pattern (LBP) and DWT is proposed for image authentication. In this method, the LBPpattern of low frequency wavelet coefficients is adopted as a feature watermark, and it is inserted into the leastsignificant bit (LSB) of the maximum pixel value in each block of host image. To guarantee the safety of theproposed algorithm, the logistic map is applied to encrypt the watermark. In addition, the locations of themaximum pixel values are stored in advance, which will be used to extract watermark on the receiving side. Due to the use of DWT, the watermarked image generated by the proposed scheme has high visual quality. Compared with other state-of-the-art watermarking methods, experimental results manifest that theproposed algorithm not only has lower watermark payloads, but also achieves good performance in tamperidentification and localization for various attacks.
Abstract
The discrete wavelet transform (DWT) has good multi-resolution decomposition characteristic and its lowfrequency component contains the basic information of an image. Based on this, a fragile watermarking usingthe local binary pattern (LBP) and DWT is proposed for image authentication. In this method, the LBPpattern of low frequency wavelet coefficients is adopted as a feature watermark, and it is inserted into the leastsignificant bit (LSB) of the maximum pixel value in each block of host image. To guarantee the safety of theproposed algorithm, the logistic map is applied to encrypt the watermark. In addition, the locations of themaximum pixel values are stored in advance, which will be used to extract watermark on the receiving side. Due to the use of DWT, the watermarked image generated by the proposed scheme has high visual quality. Compared with other state-of-the-art watermarking methods, experimental results manifest that theproposed algorithm not only has lower watermark payloads, but also achieves good performance in tamperidentification and localization for various attacks.
참고문헌 (18)
- G. C. Langelaar, "Watermarking digital image and video data: A state-of-the-art overview", IEEE Signal Processing Magazine, 17(5), pp.20~46 (2000)
- H. Nyeem, "Digital image watermarking: Its formal model, fundamental properties and possible attacks", EURASIP Journal on Advances in Signal Processing, 2014(1), pp.1~22 (2014)[DOI]
- T. Hai, "Robust image watermarking theories and techniques: A review", Journal of Applied Research and Technology, 12(1), pp.122~138 (2014)[DOI]
- K. Sreenivas, "Fragile watermarking schemes for image authentication: A survey", International Journal of Machine Learning and Cybernetics, pp.1~26 (2017)[DOI]
- S. Walton, "Information authentication for a slippery new age", Dr. Dobb's Journal, 20(4), pp.18~26 (1995)
- S. H. Liu, "An image fragile watermark scheme based on chaotic image pattern and pixel-pairs", Applied Mathematics and Computation, 185(2), pp.869~882 (2007)[DOI]
- S. Rawat, "A chaotic system based fragile watermarking scheme for image tamper detection", AEU - International Journal of Electronics and Communications, 65(10), pp.840~847 (2011)[DOI]
- L. Teng, "Cryptanalysis and improvement of a chaotic system based fragile watermarking scheme", AEU - International Journal of Electronics and Communications, 67(6), pp.540~547 (2013)[DOI]
- W. Y. Zhang, "Semi-fragile spatial watermarking based on local binary pattern operators", Optics Communications, 284(16-17), pp.3904~3912 (2011)[DOI]
- J. D. Chang, "LBP-based fragile watermarking scheme for image tamper detection and recovery", Proceedings of the IEEE International Symposium on Next-Generation Electronics, pp.173~176 (2013)
- O. Benrhouma, "Chaotic watermark for blind forgery detection in images", Multimedia Tools and Applications, 75(14), pp.8695~8718 (2016)[DOI]
- R. O. Preda, "Semi-fragile watermarking for image authentication with sensitive tamper localization in the wavelet domain", Measurement, 46(1), pp.367~373 (2013)[DOI]
- T. Ojala, "A comparative study of texture measures with classification based on feature distributions", Pattern Recognition, 29(1), pp.51~59 (1996)[DOI]
- Z. P. Dan, "An improved local binary pattern for texture classification", Optik, 125(20), pp.6320~6324 (2014)[DOI]
- B. Yang, "A comparative study on local binary pattern (LBP) based face recognition: LBP histogram versus LBP image", Neurocomputing, 120, pp.365~379 (2013)[DOI]
- H. Shi, "Secure variable-capacity self-recovery watermarking scheme", Multimedia Tools and Applications, 76(5), pp.6941~6972 (2017)[DOI]
- G. Bhatnagar, "A new robust reference watermarking scheme based on DWT-SVD", Computer Standards and Interfaces, 31(5), pp.1002~1013 (2009)[DOI]
- H. Zhang, "Fragile watermarking for image authentication using the characteristic of SVD", Algorithms, 10(1) (2017)