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To overcome the weakness of the wavelet analysis which is unable to extract curve features of the face image, this paper applies a new multiscale geometric analysis tool - curvelet transform, for facial processing and feature extraction. A new approach based on curvelet transform and subband weighted fusion algorithm is proposed for face recognition. A novel method based on curvelet transform and...
An effective algorithm for detecting QRS wave group was presented. The ECG signal is de-composed with the equivalent filter of a biorthogonal spline wavelet by Mallat pyramid decomposition. The signal singularity's Lipschitz exponent was used to analyze the relationship between the signal singularity (peak R) and the zero-crossing point of the modulus maximum pair of its wavelet transform,the Biorthogonal...
Mammography is the most effective method for the early diagnosis and treatment of breast Cancer diseases. However, data sets collected by image sensors are generally contaminated by noise. This ensures the need for image enhancement to aid interpretation. This paper introduces an efficient enhancement algorithm of digital mammograms based on wavelet analysis and modified mathematical morphology. In...
The present article focuses on the classification of fingerprints. Our aim goal is to unify the process of fingerprint compression, classification and identification. The well known methods suited to these tasks are based on WSQ (Wavelet Scalar Quantization) for compression, Gabor filters for classification and minutiae matching for identification. We propose to use Block Ridgelet Transform (BRT)...
The present work introduces a new ECG delineator, based on the Phasor Transform, which is characterized by its robustness, low computational cost and mathematical simplicity. The method converts each instantaneous ECG sample into a phasor, thus being able to deal very precisely with P and T waves, which are of notably lower amplitude than the QRS complex. Initially, the method relies on the detection...
The analysis of the electrocardiogram (ECG) is widely used for diagnosing many cardiac diseases. Since most of the clinically useful information in the ECG is found in characteristic wave peaks and boundaries, a significant amount of research effort has been devoted to the development of accurate and robust algorithms for automatic detection of the major ECG characteristic waves (i.e., the QRS complex,...
In this paper, we propose a novel feature extraction scheme based on the multi-resolution curvelet transform for face recognition. The obtained curvelet coefficients act as the feature set for classification, and are used to train the ensemble-based discriminant learning approach, capable of taking advantage of both the boosting and LDA (BLDA) techniques. The proposed method CV-BLDA has been extensively...
The study on streaming data is one of the hot topics among the database field recently. Unlike traditional data sets, stream data arrive continuously and they are fast changing, massive, possibly unpredictable. These characteristics of data stream determine that only approximate queries on them are proper. The key of approximate query is to construct a synopsis data structure far smaller than the...
Feature extraction algorithm is a very important component of any retrieval scheme. We propose M-band Wavelet Transform based feature extraction algorithm in this paper. The MtimesM sub-bands are used as primitive features, over which energies computed in a neighborhood are taken as the features for each pixel of the image. These features are clustered using FCM to obtain image signature for similarity...
A new algorithm of QT interval measurement based on multiscale morphological derivative transform (MMDT) was described in this paper. After detection of QRS complex based on MMDT, we classified the waveform into four types based on its morphological characteristics and the optimum strategy for each type was described to detect the onset of Q wave. By introducing the 'wing' function, two referenced...
In this paper, the investigation on using the proposed modified LBG algorithm for the image retrieval system is presented. The proposed algorithm transforms an image into multi-layer bitstream, the base layer and enhancement layer bitstream. Then the multi-layer bitstream is coded with modified LBG algorithm using partial search partial distortion for coding the wavelet coefficients to speed up the...
This paper introduces a face recognition method based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is used to extract features from face images. DT-CWT uses similar kernels with Gabor wavelets and is a computationally cheaper way of extracting Gabor-like features. Principal Component Analysis (PCA) which is a linear dimensionality reduction technique, that attempts to represent data...
Performance of a face recognition system has not been satisfied due to the illumination variation on facial image. Thus, there were many works that dealing with illumination compensation in face recognition in the past decades. One of the important techniques is to remove the illumination component based on the illumination reflectance model. In this paper, a facial image illumination invariant algorithm...
This paper identifies a novel feature space to address the problem of human face recognition from still images. This is based on the PCA space of the features extracted by a new multiresolution analysis tool called Fast Discrete Curvelet Transform. Curvelet Transform has better directional and edge representation abilities than widely used wavelet transform. Inspired by these attractive attributes...
A wavelet-based electrocardiogram (ECG) compression algorithm is proposed in this paper. The proposed algorithm reduces the bit rate of ECG and preserves its main clinically diagnostic features intact by minimizing reconstructed signal distortion. The original signal is divided into blocks and each block goes through a discrete wavelet transform. A threshold based on energy packing efficiency of the...
Face recognition using cubic B-spline wavelet transform is proposed in this paper. The proposed scheme is based on the analysis of face recognition using wavelet transform and the viewpoint that detail subbands after wavelet transform also have a lot of feature information. Then, the feasibility of a new application that cubic B-spline wavelet use Mallat algorithm to decompose an image under some...
In this paper, we introduce a face recognition approach based on the contourlet transform and support vector machine, which takes technological advantages of both support vector machine and the contourlet transform for feature extraction. The contributions of this paper include the following aspects: (1) support vector machine is successfully applied to face recognition by using the contourlet transform...
In this paper, we discuss a face recognition scheme by subspace analysis of 2D log-Gabor wavelets features. In which, an input face image is firstly decomposed with a set of two dimensional log-Gabor wavelets (2D-LGWs) localized with respect to spatial location, orientation and frequency. Based on complex responses of filters, local energy model (LEM) is used to represent log-Gabor features (LGFs)...
Discriminative common vectors is one of the most successful methods which overcome the small sample size case in Fisher??s linear discriminant analysis. But when we directly use DCV to reduce the dimensions of the ear images, the computational expense of training is still relatively large. A new method is proposed in this paper that the low frequency sub-images are obtained by utilizing two-dimensional...
In this work, we address the problem of multichannel image retrieval in the compressed wavelet-based domain. A wavelet transform is applied to each component. Then, two approaches are applied to extract features from the multiresolution representations. In the first one, the wavelet coefficients of each component are considered as mutually independent and hence, features are separately computed. In...
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