scholarly journals ASSAS: An automatic smart students attendance system based on normalized cross-correlation

2021 ◽  
Vol 10 (2) ◽  
pp. 732-741
Author(s):  
Ruaa H. Ali Al-Mallah ◽  
Dheyaa Alhelal ◽  
Razan Abdulhammed

A smart student attendance system (SSAS) is presented in this paper. The system is divided into two phases: hardware and software. The Hardware phase is implemented based on Arduino's camera while the software phase is achieved by using image processing with face recognition depended on the cross-correlation technique. In comparison with traditional attendance systems, roll call, and sign-in sheet, the proposed system is faster and more reliable (because there is no action needed by a human being who by its nature makes mistakes). At the same time, it is cheaper when compared with other automatic attendance systems. The proposed system provides a faster, cheaper and reachable system for an automatic smart student attendance that monitors and generates attendance report automatically.

Author(s):  
L. Fang ◽  
U. Stilla

In this paper, the impacts of the non-glacier information in the template window used in cross-correlation calculation for 2D motion estimation of glaciers are discussed and illustrated by the example of the Taku glacier, which is the biggest glacier in the Juneau Icefield, Alaska. For this, the glacier motion maps are extracted by the traditional normalized cross-correlation technique and the masked cross-correlation method, which uses a manually generated binary mask to threshold the non-glacier pixels, based on geocoded high resolution TerraSAR-X images. Based on the comparison of the different results, it was found that without the disturbing information (e.g., mountain, water) the accuracy of the cross-correlation of sequential patches in masked cross-correlation method is improved and the estimation results are much more reasonable, which respect the law that glacier flows like a river with higher velocity in the middle and than that in the sides.


2012 ◽  
Vol 8 (S295) ◽  
pp. 105-108
Author(s):  
William G. Hartley ◽  
Omar Almaini ◽  
Alice Mortlock ◽  
Chris Conselice ◽  

AbstractWe use the UKIDSS Ultra-Deep Survey, the deepest degree-scale near-infrared survey to date, to investigate the clustering of star-forming and passive galaxies to z ~ 3.5. Our new measurements include the first determination of the clustering for passive galaxies at z > 2, which we achieve using a cross-correlation technique. We find that passive galaxies are the most strongly clustered, typically hosted by massive dark matter halos with Mhalo > 1013 M⊙ irrespective of redshift or stellar mass. Our findings are consistent with models in which a critical halo mass determines the transition from star-forming to passive galaxies.


2009 ◽  
Vol 63 (11) ◽  
pp. 1197-1203 ◽  
Author(s):  
E. D. Emmons ◽  
A. Tripathi ◽  
J. A. Guicheteau ◽  
S. D. Christesen ◽  
A. W. Fountain

Raman chemical imaging (RCI) has been used to detect and identify explosives in contaminated fingerprints. Bright-field imaging is used to identify regions of interest within a fingerprint, which can then be examined to determine their chemical composition using RCI and fluorescence imaging. Results are presented where explosives in contaminated fingerprints are identified and their spatial distributions are obtained. Identification of explosives is obtained using Pearson's cosine cross-correlation technique using the characteristic region (500–1850 cm−1) of the spectrum. This study shows the ability to identify explosives nondestructively so that the fingerprint remains intact for further biometric analysis. Prospects for forensic examination of contaminated fingerprints are discussed.


2021 ◽  
Author(s):  
Alexandre Allil ◽  
Fábio Dutra ◽  
Cesar Cosenza Carvalho ◽  
Alex Dante ◽  
Regina Allil ◽  
...  

2020 ◽  
Vol 495 (2) ◽  
pp. 1706-1723 ◽  
Author(s):  
Richard A Battye ◽  
Michael L Brown ◽  
Caitlin M Casey ◽  
Ian Harrison ◽  
Neal J Jackson ◽  
...  

ABSTRACT The SuperCLuster Assisted Shear Survey (SuperCLASS) is a legacy programme using the e-MERLIN interferometric array. The aim is to observe the sky at L-band (1.4 GHz) to a r.m.s. of $7\, \mu {\rm Jy}\,$beam−1 over an area of $\sim 1\, {\rm deg}^2$ centred on the Abell 981 supercluster. The main scientific objectives of the project are: (i) to detect the effects of weak lensing in the radio in preparation for similar measurements with the Square Kilometre Array (SKA); (ii) an extinction free census of star formation and AGN activity out to z ∼ 1. In this paper we give an overview of the project including the science goals and multiwavelength coverage before presenting the first data release. We have analysed around 400 h of e-MERLIN data allowing us to create a Data Release 1 (DR1) mosaic of $\sim 0.26\, {\rm deg}^2$ to the full depth. These observations have been supplemented with complementary radio observations from the Karl G. Jansky Very Large Array (VLA) and optical/near infrared observations taken with the Subaru, Canada-France-Hawaii, and Spitzer Telescopes. The main data product is a catalogue of 887 sources detected by the VLA, of which 395 are detected by e-MERLIN and 197 of these are resolved. We have investigated the size, flux, and spectral index properties of these sources finding them compatible with previous studies. Preliminary photometric redshifts, and an assessment of galaxy shapes measured in the radio data, combined with a radio-optical cross-correlation technique probing cosmic shear in a supercluster environment, are presented in companion papers.


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