Texture classification has played an important role in many real life applications. Now, classification based on wavelet transform is being very popular. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Recently, ridgelet transform which deal effectively with line singularities in 2-D is introduced. But images oft...

Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial expression recognition, and the like. This paper presents a profile face detection algorithm based on curvelet features, as curvelet transform offers good directional representation and can capture edge information in human face from different a...

Computed tomography (CT) image-based medical recognition is extensively used for COVID as it improves and scanning rate. A method intelligent compression system-based vision computing CT (ICRS-VC-COVID) was developed. The proposed system first preprocesses lung images. Segmentation then to split the image into two regions: nonregion of interest (NROI) with fractal lossy region context tree weig...

This paper introduces curvelet transform and gradient vector flow (GVF) snake to improvement accuracy in edge detection of waterway from remote sensing images. Multi-scale geometric analysis (MGA) is booming hot research topic in recent years, which aims to obtain flexible, fast and effective signal processing algorithms through efficient approximation and characterization for the inherent geom...

In this paper, we proposed a technique for facial expression representation based on combination of Curvelet Transform and Complete Local Binary Pattern (CLBP). The curvelet transform offers improved directional capability, better ability to represent edges and other singularities along curves as compared to other traditional multiscale transforms. Hence, we transform original face images to fr...

As a latest multiresolution analysis method, curvelet transform has improved directional elements with anisotropy and better ability to represent sparsely edges and other singularities along curves. To reduce the dimensionality of facial image and improve the recognition rate, a face recognition system based on curvelet transform and Least Square Support Vector Machine (LS-SVM) has been develop...

We develop an efficient MRI denoising algorithm based on sparse representation and curvelet transform with variance stabilizing transformation framework. By using sparse representation, a MR image is decomposed into a sparsest coefficients matrix with more no of zeros. Curvelet transform is directional in nature and it preserves the important edge and texture details of MR images. In order to g...

In this paper, a denoising and binarization scheme of document images corrupted by white Gaussian noise and Impulse noise is presented using Curvelet Transform. The ability of sparse representation and edge preservation of Curvelet transform is utilized. Impulse noise gets added during document scanning or after binarization of scanned document images. White Gaussian noise corrupts the document...

Realization of focus Speakers produced words differently in the two focus conditions Acoustic features indicate high word prominence Classification Experiments Discrimination of two focus classes with ~65% correct for individual features (acoustic or visual) Exception f0: 65-83% (depending on speaker) Exception nose features: at chance level Significant AV gain when combining energy and FFT or ...

The Truncated Fourier Transform (tft) is a variation of the Discrete Fourier Transform (dft/fft) that allows for input vectors that do not have length 2 n for n a positive integer. We present the univariate version of the tft, originally due to Joris van der Hoeven, heavily illustrating the presentation in order to make these methods accessible to a broader audience.