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The common human skin disease called ringworm is investigated in the light of computer vision. Two distinct methodologies are developed for its detection. The first methodology implements three-level multi-wavelet decomposition of the skin images and ...

Face pose estimation plays important roles in broad applications such as visual based surveillance, face authentication, human-computer intelligent interactions, etc. However, face pose estimation is also a challenge issue, especially under complicated ...

Conventional gait recognition schemes has poor recognition accuracies in presence of covariates. It is mainly due to ineffective and inefficient representation and discriminative feature extraction schemes. The paper presents new technique to extract ...

A recently developed approach, called “empirical wavelet transform,” aims to build one-dimensional (1D) adaptive wavelet frames accordingly to the analyzed signal. In this paper, we present several extensions of this approach to two-dimensional (2D) signals ...

The assessment of boar sperm head images according to their acrosome status is a very important task in the veterinary field. Unfortunately it can only be performed manually, which is slow, non-objective and expensive. It is important to provide ...

An implementation of the discrete curvelet transform is proposed in this work. The transform is based on and has the same order of complexity as the Fast Fourier Transform (FFT). The discrete curvelet functions are defined by a parameterized family of ...

Contrast harmonic imaging technology has been greatly developed in recent years for its better performance compared with tissue harmonic imaging. The unique imaging mode of contrast harmonic makes it possible to detect and predict the character of ...

This paper address issues that arise in copyright protection systems of digital images, which employ blind watermark verification structures in the curvelet domain. First, we observe that statistical distribution with heavy algebraic tails, such as the ...

In this paper, a robust non-blind watermarking scheme based on Curvelet transform is proposed. This work extends the work proposed by Leung [1] to increase the quality of watermarked image. The proposed algorithm modifies the watermark extracting rule ...

In this paper, we propose a new general Quality Assessment method based on the curvelet transform, called Curvelet No-Reference (CNR) model, which can estimate levels of noise, blur and JPEG 2000 compression of natural images. The peak coordinate of the ...

In this paper we proposed new offline signature recognition based on the three different kinds of feature extractors, wavelet, curvelet and contourlet transform. The curvature and orientation of a signature image was used as feature. We utilized Support ...

This paper reports an information-theoretic analysis of the dependencies that exist between curvelet coefficients. We show that strong dependencies exist in local intra-band micro-neighborhoods, and that the shape of these neighborhoods is highly ...

In this paper, we introduced a class of directional filter banks (DFBs) having the previously proposed uniform DFB (uDFB) as a special case. Except for the uDFB, each DFB in this class can be used to decompose an image yielding up to 12 directions while ...

The separation of image content into semantic parts plays a vital role in applications such as compression, enhancement, restoration, and more. In recent years, several pioneering works suggested such a separation be based on variational formulation and ...

Currently, it appears that the best method for non-Gaussianity detection in the cosmic microwave background (CMB) consists in calculating the kurtosis of the wavelet coefficients. We know that wavelet-kurtosis outperforms other methods such as the ...

We propose in this paper a new deconvolution approach, which uses both the wavelet transform and the curvelet transform in order to benefit from the advantages of each. We illustrate the results with simulations.