@article {18234,
	title = {Joint security and robustness enhancement for quantization based data embedding},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {13},
	year = {2003},
	month = {2003/08//},
	pages = {831 - 841},
	abstract = {The paper studies joint security and robustness enhancement of quantization-based data embedding for multimedia authentication applications. We present an analysis showing that through a nontrivial run lookup table (LUT) that maps quantized multimedia features randomly to binary data, the probability of detection error can be considerably smaller than the traditional quantization embedding. We quantify the security strength of LUT embedding and enhance its robustness through distortion compensation. Introducing a joint security and capacity measure, we show that the proposed distortion-compensated LUT embedding provides joint enhancement of security and robustness over the traditional quantization embedding.},
	keywords = {(signal);, authentication;, binary, compensation;, data, data;, DETECTION, digital, distortion, distortion;, embedding;, encapsulation;, enhancement;, error, features;, hiding;, lookup, lookup;, LUT;, message, multimedia, nontrivial, probability;, quantisation, quantization, quantized, Robustness, run, Security, statistics;, systems;, table, table;, watermarking;},
	isbn = {1051-8215},
	doi = {10.1109/TCSVT.2003.815951},
	author = {Wu,M.}
}
@conference {18235,
	title = {Joint security robustness enhancement for quantization embedding},
	booktitle = {Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on},
	volume = {2},
	year = {2003},
	month = {2003/09//},
	pages = {II - 483-6 vol.3 - II - 483-6 vol.3},
	abstract = {This paper studies joint security and robustness enhancement of quantization based data embedding for multimedia authentication applications. We present analysis showing that through a lookup table (LUT) of nontrivial run that maps quantized multimedia features randomly to binary data, the detection error probability can be considerably smaller than the traditional quantization embedding. We quantify the security strength of LUT embedding and enhance its robustness through distortion compensation. Introducing a joint security and capacity measure, we show that the proposed distortion compensated LUT embedding provides joint enhancement of security and robustness over the traditional quantization embedding.},
	keywords = {applications;, Authentication, authentication;, binary, communication;, data, data;, embedding;, error, joint, lookup, lookup;, message, multimedia, probability;, security;, statistics;, table, table;, watermarking;},
	doi = {10.1109/ICIP.2003.1246722},
	author = {Wu,M.}
}
@conference {18290,
	title = {Watermarking for image authentication},
	booktitle = {Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on},
	volume = {2},
	year = {1998},
	month = {1998/10//},
	pages = {437 -441 vol.2 - 437 -441 vol.2},
	abstract = {A data embedding method is proposed for image authentication based on table look-up in frequency domain. A visually meaningful watermark and a set of simple features are embedded invisibly in the marked image, which can be stored in the compressed form. The scheme can detect and localize alterations of the original image, such as the tampering of images exported from a digital camera},
	keywords = {alterations, analysis;image, analysis;message, authentication;image, authentication;table, camera;frequency, coding;image, colour, compression;frequency-domain, detection;alterations, domain;image, EMBEDDING, image, image;compressed, image;ownership, localisation;color, look-up;watermarking;data, lookup;, method;digital, protection;table, storage;data, tampering;marked},
	doi = {10.1109/ICIP.1998.723413},
	author = {M. Wu and Liu,Bede}
}
@article {14890,
	title = {The space requirements of indexing under perspective projections},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {18},
	year = {1996},
	month = {1996/03//},
	pages = {330 - 333},
	abstract = {Object recognition systems can be made more efficient through the use of table lookup to match features. The cost of this indexing process depends on the space required to represent groups of model features in such a lookup table. We determine the space required to perform indexing of arbitrary sets of 3D model points for lookup from a single 2D image formed under perspective projection. We show that in this case, one must use a 3D surface to represent model groups, and we provide an analytic description of such a surface. This is in contrast to the cases of scaled-orthographic or affine projection, in which only a 2D surface is required to represent a group of model features. This demonstrates a fundamental way in which the recognition of objects under perspective projection is more complex than is recognition under other projection models},
	keywords = {2D, complexity;feature, complexity;table, extraction;image, hashing;indexing, image, images;3D, lookup;, lookup;computational, matching;geometric, matching;indexing;object, model, points;feature, process;invariants;object, processing;table, projections;space, recognition;perspective, recognition;stereo},
	isbn = {0162-8828},
	doi = {10.1109/34.485561},
	author = {Jacobs, David W.}
}
@conference {14837,
	title = {Space efficient 3-D model indexing},
	booktitle = {Computer Vision and Pattern Recognition, 1992. Proceedings CVPR {\textquoteright}92., 1992 IEEE Computer Society Conference on},
	year = {1992},
	month = {1992/06//},
	pages = {439 - 444},
	abstract = {It is shown that the set of 2-D images produced by a group of 3-D point features of a rigid model can be optimally represented with two lines in two high-dimensional spaces. This result is used to match images and model groups by table lookup. The table is efficiently built and accessed through analytic methods that account for the effect of sensing error. In real images, it reduces the set of potential matches by a factor of several thousand. This representation of a model{\textquoteright}s images is used to analyze two other approaches to recognition. It is determined when invariants exist in several domains, and it is shown that there is an infinite set of qualitatively similar nonaccidental properties},
	keywords = {3-D, error;table, features;sensing, indexing;3-D, lookup;, lookup;image, model, point, processing;table},
	doi = {10.1109/CVPR.1992.223153},
	author = {Jacobs, David W.}
}
@conference {14835,
	title = {Model group indexing for recognition},
	booktitle = {Computer Vision and Pattern Recognition, 1991. Proceedings CVPR {\textquoteright}91., IEEE Computer Society Conference on},
	year = {1991},
	month = {1991/06//},
	pages = {4 - 9},
	abstract = {It is shown that an index space can be a powerful tool for reducing the image-model match search by a factor of <e1>k</e1><sup>G-3 </sup>, but only when accompanied by some mechanism, such as grouping, that prevents the system from having to consider all matches between image groups of size G and model groups of size <e1>G</e1>. It is also shown that if image groups are to index a single point at recognition time, then the index space must contain pointers to each model group over a 2-D sheet, and should therefore be 2<e1>G</e1>-4 dimensional. A simple indexing system has been implemented to demonstrate these concepts, and a series of experiments have been conducted to investigate the tradeoffs between space and time. They indicate that the speedups are achievable, but require a large amount of space},
	keywords = {2-D, dimensional;image, group, groups;image-model, indexing;pattern, lookup;, match, pattern, recognition;data, recognition;pointers;computer, search;index, sheet;2G-4, space;indexing, structures;table, system;model, vision;computerised},
	doi = {10.1109/CVPR.1991.139652},
	author = {Clemens,D. T and Jacobs, David W.}
}
