Results 151 to 160 of about 1,320 (180)

Fingerprint Compression by Ridgelet Transform

2008 IEEE International Symposium on Signal Processing and Information Technology, 2008
In the present paper, a concept of compression using block ridgelet transform is introduced. This kind of analysis/synthesis fingerprint representation takes the form of basis elements which exhibit very high directional sensitivity and are highly anisotropic.
Abdelhak Ouanane, Amina Serir
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Local norm features based on ridgelets transform

Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
We propose a set of shape descriptors for image retrieval of graphic documents based on the ridgelets transform, which can be seen as a combination of the Radon transform and the wavelets transform. It is especially well suited to detect linear features, the most relevant features in graphic documents.
Oriol Ramos Terrades, Ernest Valveny
openaire   +1 more source

Image enhancement by curvelet, ridgelet, and wavelet transform

SPIE Proceedings, 2010
Image Processing always aims at extracting maximum information from an image. To achieve this we have to analyze the image completely along its periphery. But the parts of an image are hardly straight, they contain continuously varying slopes. Wavelet based image processing gives low resolution when the image has largely varying slopes and they give
Vinay Mishra, Pallavi Parlewar
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EXTENDED RIDGELET TRANSFORM ON DISTRIBUTIONS AND BOEHMIANS

Asian-European Journal of Mathematics, 2011
The ridgelet transform is extended to the space of Schwartz distributions and to the space of C∞-Boehmians consistent with the classical Ridgelet transform on the space of square integrable Boehmians. The properties of the ridgelet transform like linearity, injectivity, surjectivity and continuity with respect to two notions of convergence are ...
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Iris recognition using Ridgelet transform

2011 INTERNATIONAL CONFERENCE ON RECENT ADVANCEMENTS IN ELECTRICAL, ELECTRONICS AND CONTROL ENGINEERING, 2011
Iris Recognition is a reliable biometric identification system that uses fine textures of the Iris for person identification and verification. This paper presents a novel algorithm for accurate iris recognition using Ridgelet transform. In this work, the pupil and limbic boundaries are detected by using the equation of circle.
S. Arivazhagan, S. Shobana Priyadharshini, J. Raja Sekar   +2 more
openaire   +1 more source

Rotation Invariant Texture Classification with Ridgelet Transform and Fourier Transform

2006 International Conference on Image Processing, 2006
The features extracted from traditional wavelet transform have been successfully applied to texture classification. However, most wavelet features are not invariant to image rotation. This paper proposes a new rotation invariant feature based on the combination of ridgelet, a directional non-separable wavelet transform, and Fourier transforms.
Ke Huang 0005, Selin Aviyente
openaire   +1 more source

FFRT: A Fast Finite Ridgelet Transform for Radiative Transport

Multiscale Modeling & Simulation, 2015
This paper introduces an FFT-based implementation of a fast finite ridgelet transform which we call FFRT. Inspired by recent work where it was shown that ridgelet discretizations of linear transport equations can be easily preconditioned by diagonal preconditioning, we use the FFRT for the numerical solution of such equations. Combining this FFRT-based
Simon Etter, Philipp Grohs, Axel Obermeier   +2 more
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A vlsi architecture for finite ridgelet transform

2003 46th Midwest Symposium on Circuits and Systems, 2006
This paper presents a VLSI architecture for the finite ridgelet transform (FRIT). The proposed architecture has been partitioned into two stages. First stage computes the finite Radon transform (FRAT) coefficients and the second stage computes 1-D discrete wavelet transform (DWT) coefficients.
C.A. Rahman, W. Badawy
openaire   +1 more source

Sliced Ridgelet Transform for Image Denoising

2006 IEEE 12th Digital Signal Processing Workshop & 4th IEEE Signal Processing Education Workshop, 2006
Image denoising based on curvelet transforms gives better results than image denoising based on the standard ridgelet transforms. This paper introduces an approach for image denoising that is based on ridgelets computed in a localized manner and that is computationally less intensive than curvelets, but with similar denoising performance.
A. V. Ranganathan, R. Von Borries
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Indexing Technical Symbols Using Ridgelets Transform

2004
This paper presents a new use of the Ridgelets Transform as a multiscale method for indexing linear symbols in graphic documents. The Ridgelets Transform is useful to detect linear singularities in images. Therefore, it can be used to get a good representation of linear symbols.
Oriol Ramos Terrades, Ernest Valveny
openaire   +1 more source