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EZ-Sketching: Three-Level Optimization for Error-Tolerant Image Tracing

by Qingkun Su, Wing Ho, Andy Li, Jue Wang, Hongbo Fu
"... b c e fd Figure 1: The proposed system automatically refines sketch lines (a, c, e) (created by different users) roughly traced over a single image in a three-level optimization framework. The refined sketches (b, d, f) show closer resemblance to the traced images and are often aesthetically more pl ..."
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b c e fd Figure 1: The proposed system automatically refines sketch lines (a, c, e) (created by different users) roughly traced over a single image in a three-level optimization framework. The refined sketches (b, d, f) show closer resemblance to the traced images and are often aesthetically more

Base-calling of automated sequencer traces using phred. I. Accuracy Assessment

by Brent Ewing, Ladeana Hillier, Michael C. Wendl, Phil Green - GENOME RES , 1998
"... The availability of massive amounts of DNA sequence information has begun to revolutionize the practice of biology. As a result, current large-scale sequencing output, while impressive, is not adequate to keep pace with growing demand and, in particular, is far short of what will be required to obta ..."
Abstract - Cited by 1602 (4 self) - Add to MetaCart
improved accuracy of the data processing software and reliable accuracy measures to reduce the need for human involvement in error correction and make human review more efficient. Here, we describe one step toward that goal: a base-calling program for automated sequencer traces, phred, with improved

Using Discriminant Eigenfeatures for Image Retrieval

by Daniel L. Swets, John Weng , 1996
"... This paper describes the automatic selection of features from an image training set using the theories of multi-dimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for view-based class retrieval ..."
Abstract - Cited by 504 (15 self) - Add to MetaCart
This paper describes the automatic selection of features from an image training set using the theories of multi-dimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for view-based class

Image Quilting for Texture Synthesis and Transfer

by Alexei A. Efros , William T. Freeman , 2001
"... We present a simple image-based method of generating novel visual appearance in which a new image is synthesized by stitching together small patches of existing images. We call this process image quilting. First, we use quilting as a fast and very simple texture synthesis algorithm which produces s ..."
Abstract - Cited by 697 (19 self) - Add to MetaCart
We present a simple image-based method of generating novel visual appearance in which a new image is synthesized by stitching together small patches of existing images. We call this process image quilting. First, we use quilting as a fast and very simple texture synthesis algorithm which produces

Image registration methods: a survey

by Barbara Zitová, Jan Flusser - IMAGE AND VISION COMPUTING , 2003
"... This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align t ..."
Abstract - Cited by 734 (9 self) - Add to MetaCart
This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align

Efficient and Effective Querying by Image Content

by C. Faloutsos, W. Equitz, M. Flickner, W. Niblack, D. Petkovic, R. Barber - Journal of Intelligent Information Systems , 1994
"... In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include med ..."
Abstract - Cited by 500 (13 self) - Add to MetaCart
In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include

A Survey of Medical Image Registration

by J. B. Antoine Maintz, Max A. Viergever , 1998
"... The purpose of this chapter is to present a survey of recent publications concerning medical image registration techniques. These publications will be classified according to a model based on nine salient criteria, the main dichotomy of which is extrinsic versus intrinsic methods The statistics of t ..."
Abstract - Cited by 540 (5 self) - Add to MetaCart
The purpose of this chapter is to present a survey of recent publications concerning medical image registration techniques. These publications will be classified according to a model based on nine salient criteria, the main dichotomy of which is extrinsic versus intrinsic methods The statistics

Multimodality Image Registration by Maximization of Mutual Information

by Frederik Maes, André Collignon, Dirk Vandermeulen, Guy Marchal, Paul Suetens - IEEE TRANSACTIONS ON MEDICAL IMAGING , 1997
"... A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or in ..."
Abstract - Cited by 777 (9 self) - Add to MetaCart
solution, while robustness is evaluated with respect to implementation issues, such as interpolation and optimization, and image content, including partial overlap and image degradation. Our results demonstrate that subvoxel accuracy with respect to the stereotactic reference solution can be achieved

Fuzzy extractors: How to generate strong keys from biometrics and other noisy data. Technical Report 2003/235, Cryptology ePrint archive, http://eprint.iacr.org, 2006. Previous version appeared at EUROCRYPT 2004

by Yevgeniy Dodis, Rafail Ostrovsky, Leonid Reyzin, Adam Smith - 34 [DRS07] [DS05] [EHMS00] [FJ01] Yevgeniy Dodis, Leonid Reyzin, and Adam , 2004
"... We provide formal definitions and efficient secure techniques for • turning noisy information into keys usable for any cryptographic application, and, in particular, • reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying mater ..."
Abstract - Cited by 532 (38 self) - Add to MetaCart
material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two primitives: a fuzzy extractor reliably extracts nearly uniform randomness R from its input; the extraction is error-tolerant in the sense that R will be the same even

PCA-SIFT: A more distinctive representation for local image descriptors

by Yan Ke, Rahul Sukthankar , 2004
"... Stable local feature detection and representation is a fundamental component of many image registration and object recognition algorithms. Mikolajczyk and Schmid [14] recently evaluated a variety of approaches and identified the SIFT [11] algorithm as being the most resistant to common image deforma ..."
Abstract - Cited by 572 (6 self) - Add to MetaCart
Stable local feature detection and representation is a fundamental component of many image registration and object recognition algorithms. Mikolajczyk and Schmid [14] recently evaluated a variety of approaches and identified the SIFT [11] algorithm as being the most resistant to common image
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