Fast generalized Hough transform

[[abstract]]A fast algorithm for the generalized Hough transform (GHT) based on the use of a hierarchical processing scheme and the inverse generalized Hough operation is proposed. By reducing the size of the image portion which need be processed in the proposed fast GHT, not only the computation time but also the number of processing elements for parallel processing can be reduced. The way to apply the proposed fast recursive GHT on pyramid machines is discussed. Some experimental results are also included to demonstrate the applicability of the approach

Fast Minutia-based Palmprint Matching Using CNN and Generalized Hough Transform

Due to the large number of minutiae in a palmprint, the match-ing process between two palm images is time consuming. Oneway to address this issue is aligning all palmprint images to a ref-erence image. In this paper, using convolutional neural network(CNN) and generalized Hough transform (GHT), we propose a newmethod to find the corresponding rotation and displacement be-tween any palmprint and the reference palm image. Furthermore,the proposed method is capable of distinguishing between left andright palmprint automatically which helps to speed up the match-ing process. The proposed registration method followed by minutia-cylinder code (MCC) matching algorithm has been evaluated on theTHUPALMLAB database, and the results show the superiority of ouralgorithm over most of the state-of-the-art

A method to search for long duration gravitational wave transients from isolated neutron stars using the generalized FrequencyHough

We describe a method to detect gravitational waves lasting $O(hours-days)$ emitted by young, isolated neutron stars, such as those that could form after a supernova or a binary neutron star merger, using advanced LIGO/Virgo data. The method is based on a generalization of the FrequencyHough (FH), a pipeline that performs hierarchical searches for continuous gravitational waves by mapping points in the time/frequency plane of the detector to lines in the frequency/spindown plane of the source. We show that signals whose spindowns are related to their frequencies by a power law can be transformed to coordinates where the behavior of these signals is always linear, and can therefore be searched for by the FH. We estimate the sensitivity of our search across different braking indices, and describe the portion of the parameter space we could explore in a search using varying fast Fourier Transform (FFT) lengths.Comment: 15 figure

Timely-automatic procedure for estimating the endocardial limits of the left ventricle assessed echocardiographically in clinical practice

In this paper, we propose an analytical rapid method to estimate the endocardial borders of the left ventricular walls on echocardiographic images for prospective clinical integration. The procedure was created as a diagnostic support tool for the clinician and it is based on the use of the anisotropic generalized Hough transform. Its application is guided by a Gabor-like filtering for the approximate delimitation of the region of interest without the need for computing further anatomical characteristics. The algorithm is applying directly a deformable template on the predetermined filtered region and therefore it is responsive and straightforward implementable. For accuracy considerations, we have employed a support vector machine classifier to determine the confidence level of the automated marking. The clinical tests were performed at the Cardiology Clinic of the County Emergency Hospital Timisoara and they improved the physicians perception in more than 50% of the cases. The report is concluded with medical discussions.European Union (UE)Ministerio de Economía y Competitividad (MINECO). Españ

Ship Wake Detection in SAR Images via Sparse Regularization

In order to analyse synthetic aperture radar (SAR) images of the sea surface, ship wake detection is essential for extracting information on the wake generating vessels. One possibility is to assume a linear model for wakes, in which case detection approaches are based on transforms such as Radon and Hough. These express the bright (dark) lines as peak (trough) points in the transform domain. In this paper, ship wake detection is posed as an inverse problem, which the associated cost function including a sparsity enforcing penalty, i.e. the generalized minimax concave (GMC) function. Despite being a non-convex regularizer, the GMC penalty enforces the overall cost function to be convex. The proposed solution is based on a Bayesian formulation, whereby the point estimates are recovered using maximum a posteriori (MAP) estimation. To quantify the performance of the proposed method, various types of SAR images are used, corresponding to TerraSAR-X, COSMO-SkyMed, Sentinel-1, and ALOS2. The performance of various priors in solving the proposed inverse problem is first studied by investigating the GMC along with the L1, Lp, nuclear and total variation (TV) norms. We show that the GMC achieves the best results and we subsequently study the merits of the corresponding method in comparison to two state-of-the-art approaches for ship wake detection. The results show that our proposed technique offers the best performance by achieving 80% success rate.Comment: 18 page