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Deformable models in medical image analysis: A survey

by Tim Mcinerney, Demetri Terzopoulos - Medical Image Analysis , 1996
"... This article surveys deformable models, a promising and vigorously researched computer-assisted medical image analysis technique. Among model-based techniques, deformable models offer a unique and powerful approach to image analysis that combines geometry, physics, and approximation theory. They hav ..."
Abstract - Cited by 591 (7 self) - Add to MetaCart
This article surveys deformable models, a promising and vigorously researched computer-assisted medical image analysis technique. Among model-based techniques, deformable models offer a unique and powerful approach to image analysis that combines geometry, physics, and approximation theory

Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression

by John G. Daugman , 1988
"... A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor” representations for image analysis, segmentation, and compression. These transforms are conjoint spatial/spectral representations [lo], [15], which provide a comp ..."
Abstract - Cited by 478 (8 self) - Add to MetaCart
A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor” representations for image analysis, segmentation, and compression. These transforms are conjoint spatial/spectral representations [lo], [15], which provide a

Image analysis using mathematical morphology

by Robert M. Haralick, Stanley R. Sternberg, Xinhua Zhuang - IEEE TRANS. PATTERN ANAL. MACHINE INTELL , 1987
"... For the purposes of object or defect identification required in industrial vision applications, the operations of mathematical morphology are more useful than the convolution operations employed in signal processing because the morphological operators relate directly to shape. The tutorial provided ..."
Abstract - Cited by 322 (7 self) - Add to MetaCart
For the purposes of object or defect identification required in industrial vision applications, the operations of mathematical morphology are more useful than the convolution operations employed in signal processing because the morphological operators relate directly to shape. The tutorial provided in this paper reviews both binary morphology and gray scale morphology, covering the operations of dilation, erosion, opening, and closing and their relations. Examples are given for each morphological concept and explanations are given for many of their interrelationships.

The Laplacian Pyramid as a Compact Image Code

by Peter J. Burt , Edward H. Adelson , 1983
"... We describe a technique for image encoding in which local operators of many scales but identical shape serve as the basis functions. The representation differs from established techniques in that the code elements are localized in spatial frequency as well as in space. Pixel-to-pixel correlations a ..."
Abstract - Cited by 1388 (12 self) - Add to MetaCart
, the code tends to enhance salient image features. A further advantage of the present code is that it is well suited for many image analysis tasks as well as for image compression. Fast algorithms are described for coding and decoding. A

Representing Moving Images with Layers

by John Y.A. Wang, Edward H. Adelson , 1994
"... We describe a system for representing moving images with sets of overlapping layers. Each layer contains an intensity map that defines the additive values of each pixel, along with an alpha map that serves as a mask indicating the transparency. The layers are ordered in depth and they occlude each o ..."
Abstract - Cited by 542 (11 self) - Add to MetaCart
sequences into layers using motion analysis, and we discuss how the representation may be used for image coding and other applications.

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 508 (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

Morphological grayscale reconstruction in image analysis: Applications and efficient algorithms

by Luc Vincent - IEEE Transactions on Image Processing , 1993
"... Morphological reconstruction is part of a set of image operators often referred to as geodesic. In the binary case, reconstruction simply extracts the connected components of a binary image I (the mask) which are \marked " by a (binary) image J contained in I. This transformation can be ext ..."
Abstract - Cited by 336 (3 self) - Add to MetaCart
be extended to the grayscale case, where it turns out to be extremely useful for several image analysis tasks. This paper rst provides two di erent formal de nitions of grayscale reconstruction. It then illustrates the use of grayscale reconstruction in various image processing applications and aims

Imagenet: A large-scale hierarchical image database

by Jia Deng, Wei Dong, Richard Socher, Li-jia Li, Kai Li, Li Fei-fei - In CVPR , 2009
"... The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such data can be harnessed and organized remains a critical problem. We introduce her ..."
Abstract - Cited by 840 (28 self) - Add to MetaCart
of annotated images organized by the semantic hierarchy of WordNet. This paper offers a detailed analysis of ImageNet in its current state: 12 subtrees with 5247 synsets and 3.2 million images in total. We show that ImageNet is much larger in scale and diversity and much more accurate than the current image

The Contourlet Transform: An Efficient Directional Multiresolution Image Representation

by Minh N. Do, Martin Vetterli - IEEE TRANSACTIONS ON IMAGE PROCESSING
"... The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure t ..."
Abstract - Cited by 513 (20 self) - Add to MetaCart
The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure

Scale-Space Theory in Computer Vision

by Tony Lindeberg , 1994
"... A basic problem when deriving information from measured data, such as images, originates from the fact that objects in the world, and hence image structures, exist as meaningful entities only over certain ranges of scale. "Scale-Space Theory in Computer Vision" describes a formal theory fo ..."
Abstract - Cited by 625 (21 self) - Add to MetaCart
A basic problem when deriving information from measured data, such as images, originates from the fact that objects in the world, and hence image structures, exist as meaningful entities only over certain ranges of scale. "Scale-Space Theory in Computer Vision" describes a formal theory
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