@conference {18261,
	title = {Performance of detection statistics under collusion attacks on independent multimedia fingerprints},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {1},
	year = {2003},
	month = {2003/07//},
	pages = {I - 205-8 vol.1 - I - 205-8 vol.1},
	abstract = {Digital fingerprinting is a technology for tracing the distribution of multimedia content and protecting them from unauthorized redistribution. Collusion attack is a cost effective attack against digital fingerprinting where several copies with the same content but different fingerprints are combined to remove the original fingerprints. In this paper, we consider average attack and several nonlinear collusion attacks on independent Gaussian based fingerprints, and study the detection performance of several commonly used detection statistics in the literature under collusion attacks. Observing that these detection statistics are not specifically designed for collusion scenarios and do not take into account the characteristics of the newly generated fingerprints under collusion attacks, we propose pre-processing techniques to improve the detection performance of the detection statistics under collusion attacks.},
	keywords = {analysis;, attacks;, based, collusion, content;, DETECTION, digital, fingerprint, fingerprinting;, fingerprints;, Gaussian, identification;, independent, multimedia, performance;, preprocessing, processes;, redistribution;, security;, statistical, statistics;, systems;, techniques;, Telecommunication, unauthorized},
	doi = {10.1109/ICME.2003.1220890},
	author = {Zhao,Hong and M. Wu and Wang,Z.J. and Liu,K. J.R}
}
@conference {18166,
	title = {Anti-collusion codes: multi-user and multimedia perspectives},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {2},
	year = {2002},
	month = {2002///},
	pages = {II-149 - II-152 vol.2 - II-149 - II-152 vol.2},
	abstract = {Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content, such as images and video. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cheap and effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are averaged or combined to disrupt the underlying fingerprint. We present a construction of collusion-resistant fingerprints based upon anti-collusion codes (ACC) and binary code modulation. ACC have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we build fingerprints that allow for the identification of groups of K or less colluders. We present a construction of binary-valued ACC under the logical AND operation using the theory of combinatorial designs. Our code construction requires only Oscr;( radic;n) orthogonal signals to accommodate n users. We demonstrate the performance of our ACC for fingerprinting multimedia by identifying colluders through experiments using real images.},
	keywords = {and, anti-collusion, authentication;, binary, code, codes;, coding;, combinatorial, computing;, content;, data, designs;, digital, embedding;, encapsulation;, fingerprinting;, image, images;, logical, mathematics;, message, Modulation, modulation;, multimedia, operation;, performance;, watermarking;},
	doi = {10.1109/ICIP.2002.1039909},
	author = {Trappe,W. and M. Wu and Liu,K. J.R}
}
@article {12748,
	title = {Optimal edge-based shape detection},
	journal = {Image Processing, IEEE Transactions on},
	volume = {11},
	year = {2002},
	month = {2002/11//},
	pages = {1209 - 1227},
	abstract = {We propose an approach to accurately detecting two-dimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-dimensional (1-D) optimal step edge operator, which minimizes both the noise power and the mean squared error between the input and the filter output. This operator is found to be the derivative of the double exponential (DODE) function, originally derived by Ben-Arie and Rao (1994). We define an operator for shape detection by extending the DODE filter along the shape{\textquoteright}s boundary contour. The responses are accumulated at the centroid of the operator to estimate the likelihood of the presence of the given shape. This method of detecting a shape is in fact a natural extension of the task of edge detection at the pixel level to the problem of global contour detection. This simple filtering scheme also provides a tool for a systematic analysis of edge-based shape detection. We investigate how the error is propagated by the shape geometry. We have found that, under general assumptions, the operator is locally linear at the peak of the response. We compute the expected shape of the response and derive some of its statistical properties. This enables us to predict both its localization and detection performance and adjust its parameters according to imaging conditions and given performance specifications. Applications to the problem of vehicle detection in aerial images, human facial feature detection, and contour tracking in video are presented.},
	keywords = {1D, 2D, aerial, analysis;, boundary, conditions;, contour, cross, detection;, DODE, double, edge, edge-based, error, error;, exponential, extraction;, facial, feature, filter, filter;, Filtering, function;, geometry;, global, human, images;, imaging, localization, mean, methods;, NOISE, operator;, optimal, optimisation;, output;, performance;, pixel;, power;, propagation;, properties;, section;, SHAPE, square, squared, statistical, step, theory;, tracking;, two-dimensional, vehicle, video;},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2002.800896},
	author = {Moon, H. and Chellapa, Rama and Rosenfeld, A.}
}
@conference {15577,
	title = {Algorithms for fast vector quantization},
	booktitle = {Data Compression Conference, 1993. DCC {\textquoteright}93.},
	year = {1993},
	month = {1993///},
	pages = {381 - 390},
	abstract = {This paper shows that if one is willing to relax the requirement of finding the true nearest neighbor, it is possible to achieve significant improvements in running time and at only a very small loss in the performance of the vector quantizer. The authors present three algorithms for nearest neighbor searching: standard and priority <e1>k </e1>-<e1>d</e1> tree search algorithms and a neighborhood graph search algorithm in which a directed graph is constructed for the point set and edges join neighboring points},
	keywords = {algorithm;, algorithms;, directed, fast, graph, graph;, graphs;, Neighborhood, performance;, problems;, quantisation;, quantization;, running, search, time;, tree, vector},
	doi = {10.1109/DCC.1993.253111},
	author = {Arya,S. and Mount, Dave}
}
