Machine Learning for Image Processing

Image Fingerprinting



A robust image fingerprinting system using the Radon transform


Jin S. Seo, J.A. Haitsma, Ton Kalker and Chang D. Yoo


With the ever-increasing use of multimedia contents through electronic commerce and on-line services, the problems associated withth e protection of intellectual property, management of large database and indexation of content are becoming more prominent. Watermarking has been considered as efficient means to these problems. Although watermarking is a powerful tool, there are some issues with the use of it, such as the modification of the content and its security. With respect to this, identifying content itself based on its own features rather than watermarking can be an alternative solution to these problems. The aim of fingerprinting is to provide fast and reliable methods for content identification. In this paper, we present a new approach for image fingerprinting using the Radon transform to make the fingerprint robust against affine transformations. Since it is quite easy withmodern computers to apply affine transformations to audio, image and video, there is an obvious necessity for affine transformation resilient fingerprinting. Experimental results show that the proposed fingerprints are highly robust against most signal processing transformations. Besides robustness, we also address other issues such as pairwise independence, database search efficiency and key dependence of the proposed method.


Related Papers

1. Jin S. Seo, J.A. Haitsma, Ton Kalker and Chang D. Yoo, "A robust image fingerprinting system using the Radon transform," Signal Processing: Image Communication, vol. 19, no. 4, pp. 325-339, April 2004.

2. Jinho Choi, Dalwon Jang and Chang D. Yoo, "An Image Fingerprinting System Based on Color Histogram of Affine Covariant Region," in ICEIC, Cebu, Philippines, 2010.

3. Jin S. Seo, Jaap Haitsma, Ton Kalker and Chang D. Yoo, "Affine transform resilient image fingerprinting," In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Hong Kong, China, vol. 3, pp. 61-64, April 2003.