Search results for "Wavelet"
showing 10 items of 329 documents
Content based segmentation of patterned wafers
2004
We extend our previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer in- spection is based on the comparison of the same area on two neigh- boring dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, seg- mentation is required to create a mask and apply an optimal thresh- old in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. We show a method to anticipate these variation…
Optical flow estimation from multichannel spherical image decomposition
2011
The problem of optical flow estimation is largely discussed in computer vision domain for perspective images. It was also proven that, in terms of optical flow analysis from these images, we have difficulty distinguishing between some motion fields obtained with little camera motion. The omnidirectional cameras provided images with large filed of view. These images contain global information about motion and allow to remove the ambiguity present in perspective case. Nevertheless, these images contain significant radial distortions that is necessary to take into account when treating these images to estimate the motion. In this paper, we shall describe new way to compute efficient optical fl…
<title>Human cell texture analysis with quincunx spline wavelet transform</title>
1999
Wavelet transforms are efficient tools for texture analysis and classification. Separable techniques are classically used but present several drawbacks. First, diagonal coefficients contain poor information. Second, the other coefficients contain useful information only if the texture is oriented in the vertical and horizontal directions. So an approach of texture analysis by non-separable transform is proposed. An improved interscale resolution is allowed by the quincunx scheme and this analysis leads to only one detail image where no particular orientation is favored. New orthogonal isotropic filters for the decomposition are constructed by applying McClellan transform on one dimension B-…
<title>Multiresolution description of range images through 2D quincunx wavelet analysis</title>
1999
In this paper, we present a method for performing a multi- scale analysis on range images by using the wavelet transform, that is capable of revealing multi-resolution information. An accurate non-contact optical system based upon laser triangulation is used to determine the depth information of the object being scanned. The resulting range image is treated as a gray-level image by using a multi- resolution approach based on the generalization of the cascade algorithm using the quincunx wavelet transform. The quincunx wavelet assures very fine analysis. This method allows reconstruction of non-subsampled images that correspond to decompositions previously done at chosen scales. Multi-resolu…
A statistical model for magnitudes and angles of wavelet frame coefficients and its application to texture retrieval
2014
Abstract This paper presents a texture descriptor based on wavelet frame transforms. At each position in the image, and for each resolution level, we consider both vertical and horizontal wavelet detail coefficients as the components of a bivariate random vector. The magnitudes and angles of these vectors are computed. At each level the empirical histogram of magnitudes is modeled by a Generalized Gamma distribution, and the empirical histogram of angles is modeled by a different version of the von Mises distribution that accounts for histograms with 2 modes. Each texture is characterized by few parameters. A new distance is presented (based on the Kullback–Leibler divergence) that allows g…
Impact of Wavelet Kernels on Predictive Capability of Radiomic Features: A Case Study on COVID-19 Chest X-ray Images
2023
Radiomic analysis allows for the detection of imaging biomarkers supporting decision-making processes in clinical environments, from diagnosis to prognosis. Frequently, the original set of radiomic features is augmented by considering high-level features, such as wavelet transforms. However, several wavelets families (so called kernels) are able to generate different multi-resolution representations of the original image, and which of them produces more salient images is not yet clear. In this study, an in-depth analysis is performed by comparing different wavelet kernels and by evaluating their impact on predictive capabilities of radiomic models. A dataset composed of 1589 chest X-ray ima…
One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals
2021
Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…
Automated detection and localization system of myocardial infarction in single-beat ECG using Dual-Q TQWT and wavelet packet tensor decomposition
2020
Background and objective. It is challenging to conduct real-time identification of myocardial infarction (MI) due to artifact corruption and high dimensionality of multi-lead electrocardiogram (ECG). In the present study, we proposed an automated single-beat MI detection and localization system using dual-Q tunable Q-factor wavelet transformation (Dual-Q TQWT) denoising algorithm. Methods. After denoising and segmentation of ECG, a fourth-order wavelet tensor (leads × subbands × samples × beats) was constructed based on thediscretewavelet packet transform (DWPT), to represent the features considering the information of inter-beat, intra-beat, inter-frequency, and inter-lead. To reduce the t…
Quantitative Rotor Broken Bar Evaluation in Double Squirrel Cage Induction Machines under Dynamic Operating Conditions
2013
Advanced monitoring techniques leading to fault diagnosis and prediction of induction machine faults, operating under non-stationary conditions have gained strength because of its considerable influence on the operational continuation of many industrial processes. In case of rotor broken bars, fault detection based on sideband components issued from currents, flux, instantaneous control or power signals under different load conditions, may fail due to the presence of inter-bar currents that reduce the degree of rotor asymmetry, especially for double squirrel cage induction motors. But the produced core vibrations in the axial direction, can be investigated to overcome the limitation of the …
Detection of rupture lines for active scanning
2007
Corner and junction detection is an important preprocessing step in image registration, data fusion, object recognition, and many other tasks. This work deals with corner and junction detection of characteristic features of the structure resulting from cross-pattern projection. The ultimate aim is to adapt the positions and orientation of the cross-pattern projections to what has been observed. The use of this projected light pattern in the framework of active vision allows us to identify certain points of interest on 3-D objects, to directly acquire a synthesis, which thus permits simplified detection, measurement, recognition, or tracking. We present detection methods for corners and junc…