Abstract
With the rapid development of information technology, images can be easily copied, modified, and re-released. This paper proposes a copyright protection method based on the main feature of digital images by using SIFT algorithm. It aims to prevent the image which main feature information is stored in database from being abused. The innovation point is to store feature information instead of images with much redundant information, which can accelerate matching. It can be judged whether a picture infringes copyright by extracting its main feature information, then comparing with those in database. The experiment results show that this method can resist tampering attack such as JPEG compression, noise, and geometric distortion.
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References
Podilchuk, C., Zeng, W.: Image-adaptive Watermarking Using Visual Models. Selected Areas in Communications IEEE Journal on. vol. 16, no. 4, pp. 525--539 (1998)
Lowe, D.G.: Object Recognition from Local Scale-invariant Features. The Proceedings of the Seventh IEEE International Conference on Computer Vision. IEEE. vol. 2, pp. 1150--1157 (1999)
Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision. vol. 60, no. 2, pp:91--110 (2004)
Bas, P., Chassery, J.M., Macq, B.: Geometrically Invariant Watermarking Using Feature Points. IEEE Transactions on Image Processing. vol. 11, no. 9, pp.1014--1028 (2002)
Mair, E., Hager, G.D., Burschka. D., et al.: Adaptive and Generic Corner Detection Based on the Accelerated Segment Test. LNCS, vol. 6312, no. PART 2, pp. 183--196. Computer Vision - ECCV 2010. European Conference on Computer Vision. Heraklion, Crete, Greece, September 5-11, Proceedings (2010)
Lu, C.S., Liao, H.Y.M.: Multipurpose Watermarking for Image Authentication and Protection. IEEE Transactions on Image Processing. vol. 10, no.10, pp. 1579--1592 ( 2001)
Fischler, M.A., Bolles, R.C.: Random Sample Consensus: a Paradigm for Model Fitting with Application to Image Analysis and Automated Cartography. Communications of the ACM. vol. 24, no. 6, pp. 381--395 (1981)
Torr, P.H.S., Zisserman. A.: MLESAC: A New Robust Estimator with Application to Estimating Image Geometry. Computer Vision and Image Understanding. vol. 78, no. 1, pp.138--156 (2010)
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Wang, X., Yang, Z., Niu, S. (2017). Copyright Protection Method based on the Main Feature of Digital Images. In: Pan, JS., Tsai, PW., Huang, HC. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 63. Springer, Cham. https://doi.org/10.1007/978-3-319-50209-0_18
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DOI: https://doi.org/10.1007/978-3-319-50209-0_18
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