Search results for "Centroid"
showing 10 items of 37 documents
Parameter properties and stellar population of the old open cluster NGC 3960
2004
We present a $BVI$ photometric and astrometric catalogue of the open cluster NGC 3960, down to limiting magnitude $V\sim22$, obtained from observations taken with the Wide Field Imager camera at the MPG/ESO 2.2 m Telescope at La Silla. The photometry of all the stars detected in our field of view has been used to estimate a map of the strong differential reddening affecting this area. Our results indicate that, within the region where the cluster dominates, the $E(V-I)$ values range from 0.21 up to 0.78, with $E(V-I)=0.36$ ($E(B-V)=0.29$) at the nominal cluster centroid position; color excesses $E(V-I)$ up to 1 mag have been measured in the external regions of the field of view where field …
Centroid-based Cluster Analysis of HVSR Data for Seismic Microzonation
2014
Horizontal to Vertical Spectral Ratio (HVSR) datasets acquired for studies of seismic microzoning in various urban centers of Sicilian towns, have been used to test clustering analysis through a nonhierarchical centroid-based algorithm. In this context clustering techniques may be useful to identify areas with similar seismic behaviour through HVSR data. Centroid-based algorithms generally require the number of clusters, k, and the initial centroid coordinates to be specified in advance. This aspect is considered to be one of the biggest drawbacks of these algorithms. The proposed algorithm doesn’t limit the number of k clusters and choose the initial centroids automatically from the data s…
Experimental and Modeling Analyses of Human Motion Across the Static Magnetic Field of an MRI Scanner
2021
It is established that human movements in the vicinity of a permanent static magnetic field, such as those in magnetic resonance imaging (MRI) scanners induce electric fields in the human body; this raises potential severe risks of health to radiographers and cleaners exposed routinely to these fields in MRI rooms. The relevant directives and parameters, however, are based on theoretical models, and accurate studies on the simulation of the effects based on human movement data obtained in real conditions are still lacking. Two radiographers and one cleaner, familiar with MRI room activities and these directives, were gait analyzed during the execution of routine job motor tasks at different…
A real-time webcam based Eye Ball Tracking System using MATLAB
2015
Eye Ball Tracking System is a device which is intended to assist patients that cannot perform any voluntary tasks related to daily life. Patients who only can control their eyes can still communicate with the real-world using the assistive devices like one proposed in this paper. This device provides a human computer interface in order to take decisions based on their eye movement. A real time data stream is captured via webcam that transfers data serially to MATLAB. Then a sequential image processing scheme segments the iris of the eye and calculates the centroid, thereby generating control signal with the help of a reference axis. The control signals are then used to manipulate the positi…
“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids
2017
A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naive-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for this paradigm, referred to as the “Anti-Bayesian” (AB) paradigm, involves classification based on the non-central quantiles of the distributions. The first-reported work to achieve clustering using the A…
Time-Frequency Filtering for Seismic Waves Clustering
2014
This paper introduces a new technique for clustering seismic events based on processing, in time-frequency domain, the waveforms recorded by seismographs. The detection of clusters of waveforms is performed by a k-means like algorithm which analyzes, at each iteration, the time-frequency content of the signals in order to optimally remove the non discriminant components which should compromise the grouping of waveforms. This step is followed by the allocation and by the computation of the cluster centroids on the basis of the filtered signals. The effectiveness of the method is shown on a real dataset of seismic waveforms.
Detection and Isolation of Switches in Point Clouds of the German Railway Network
2015
In order to obtain an automated system of railway management, it is necessary to automatically detect, isolate and identify all switches in a point cloud which represents the railway. To realize this automated system of detection, a set of pre-processing steps is applied. The system begins by detecting and isolating tracks through application of a mask on each section of the point cloud. Then, it does a denoising through mathematical morphology and a compression in replacing a group of points by their centroid. Finally, it closes tracks holes through extrapolation. After that, the system does a low-level processing to search for all intersections between tracks, and records information on t…
Spectrum cartography using adaptive radial basis functions: Experimental validation
2017
In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The perfor…
Speech Activity Detection under Adverse Noisy Conditions at Low SNRs
2021
Speech originating from the noisy environments degrades the speech quality and intelligibility, thus reducing the human perceived Quality of Experience (QoE). For example, surveillance using drone during natural catastrophe needs an efficient speech recognition device to recognise the speech of the frozen human in presence of drone noise to save their life. Therefore, it often requires to pre-process the noisy speech in order to reduce the noise artifacts and enhance the speech. This paper detects the speech activity using Voice Activity Detection (VAD). The VAD distinguishes speech activity (speech presence) and speech inactivity (silence/noise) by extracting the speech features and compar…
Testing abnormality in the spatial arrangement of cells in the corneal endothelium using spatial point processes
2001
The study of central corneal endothelium morphology is important in Ophthalmology. Some of the pathologies that could compromise endothelial cell morphology are trauma, cataract, surgery, use of contact lenses, corneal dystrophies or degenerations. The quantitative analysis of cell shape and cellular pattern is more sensitive in detecting subtle changes in endothelial morphology than cell density measurement or cell area analysis. In this paper, the morphology of the central cornea, the most important area from the point of view of vision, is studied through an associated bivariate spatial point pattern: the centroids of the cells and the triple points, that is, the points where three diffe…