Results 131 to 140 of about 1,028 (168)

Numeral recognition using curvelet transform

2008 IEEE/ACS International Conference on Computer Systems and Applications, 2008
This paper proposes the performance of two new algorithms for digit recognition. These recognition systems are based on extracted features on the performance of image's curvelet transform & achieving standard deviation and entropy of curvelet coefficients matrix in different scales & various angels.
Farhad Mohamad Kazemi, Jalaleddin Izadian, Reihaneh Moravejian, Ehsan Mohamad Kazemi   +3 more
openaire   +1 more source

ECG steganography using curvelet transform

Biomedical Signal Processing and Control, 2015
Abstract ECG steganography allows secured transmission of patient data that are tagged to the ECG signals. Signal deterioration leading to loss of diagnosis information and inability to retrieve patient data fully are the major challenges with ECG steganography.
S. Edward Jero, Palaniappan Ramu, Ramakrishnan Swaminathan   +2 more
openaire   +1 more source

Multipurpose watermarking based on curvelet transform

2008 IEEE International Symposium on Circuits and Systems (ISCAS), 2008
Based on curvelet transform this paper embeds one leveled watermark onto significant coefficients by quantization in individual frequency scales. Watermark bits come from image HASH, which is defined in the paper. Bigger coefficients are used for watermarking for the conception that coefficient energy is proportion to its directional sensitivity and ...
Chune Zhang, L. L. Cheng, Lee-Ming Cheng, Zhengding Qiu   +3 more
openaire   +1 more source

Digital watermarking based on curvelet transform

2007 9th International Symposium on Signal Processing and Its Applications, 2007
This paper proposes a new watermarking method in the curvelet domain. The curvelet transform was developed in order to represent edges along curves much more efficiently than the traditional transforms. We apply the transform to watermarking and evaluate the effectiveness of the method.
Thai Duy Hien, Kazuyoshi Miyara, Ikeda Kei, Fath El Alem F. Ali, Yen-Wei Chen 0001, Zensho Nakao   +5 more
openaire   +1 more source

Digital Curvelet Transform for Palmprint Recognition

2004
In this paper, we present a new feature extraction method for palmprint recognition The digital curvelet transform is revised here and used to extract the palmprint features In our algorithm, we use the discrete Meyer wavelet transform to replace the “a trous” transform, then apply the ridgelet transform to each block which is subbanded after the ...
Kaifeng Dong, Guiyu Feng, Dewen Hu
openaire   +1 more source

3D discrete curvelet transform

SPIE Proceedings, 2005
In this paper, we present the first 3D discrete curvelet transform. This transform is an extension to the 2D transform described in Candes et al..1 The resulting curvelet frame preserves the important properties, such as parabolic scaling, tightness and sparse representation for singularities of codimension one.
Lexing Ying, Laurent Demanet, Emmanuel Candes   +2 more
openaire   +1 more source

Localization operators for curvelet transforms

Journal of Pseudo-Differential Operators and Applications, 2011
The authors investigate the \(L^{2}\)-boundedness of three kinds of operators such as the localization operators for high frequencies, the wavelet multipliers for low frequencies and the curvelet localization operators for all signals. Also, they present a resolution of the identity formulas for high-frequency signals and study the trace class ...
Li, Jiawei, Wong, M. W.
openaire   +2 more sources

Curvelet transform on tempered distributions

Asian-European Journal of Mathematics, 2015
The curvelet transform of a tempered distribution is defined as an infinitely differentiable function of (a, b, θ) with a polynomial growth in b. An inversion formula of the curvelet transform on tempered distributions is also obtained.
Subash Moorthy, R., Roopkumar, R.
openaire   +1 more source

Combining Curvelet Transform and Wavelet Transform for Image Denoising

2010
Wavelet transform has the good characteristic of time-frequency locality and many researches show that it can perform well for denoising in smooth and singular areas. But it isn't suitable for describing the signals, which have high dimensional singularities.
Ying Li 0017, Shengwei Zhang, Jie Hu
openaire   +1 more source

Image quality measure based on curvelet transform

10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010), 2010
This paper presents a new image quality assessment based on the curvelet decomposition. The curvelet transform is introduced for its ability to represent the curves of images at different scales and directions. Unlike existing methods, the proposed image quality assessment takes into account the geometrical content of the image at different scales and ...
Zehira Haddad, Azeddine Beghdadi, Amina Serir, Anissa Mokraoui   +3 more
openaire   +1 more source