Multilevel fractal test target: corner-point criterion for evaluating visible and digital fusion imagers

Author(s):  
Stéphane Landeau ◽  
Greggory Swiathy
Keyword(s):  
Author(s):  
Anatoly I. Ruban

Chapter 4 analyses the transition from an attached flow to a flow with local recirculation region near a corner point of a body contour. It considers both subsonic and supersonic flow regimes, and shows that the flow near a corner can be studied in the framework of the triple-deck theory. It assumes that the body surface deflection angle is small, and formulates the linearized viscous-inviscid interaction problem. Its solution is found in an analytic form. It also presents the results of the numerical solution of the full nonlinear problem. It shows how, and when, the separation region forms in the boundary layer. In conclusion, it suggests that in the subsonic flow past a concave corner, the solution is not unique.


2014 ◽  
Vol 960-961 ◽  
pp. 1100-1103
Author(s):  
Guang Bin Zhang ◽  
Hong Chun Shu ◽  
Ji Lai Yu

Wavefront identification is important for traveling based fault location. In order to improve its reliability, a novel wavefront identification method based on Harris corner detector has been proposed in this paper. The principle of single-ended traveling wave fault location was briefly introduced at first, and the features of wavefronts generated by faults on transmission lines were analyzed. The arrival of traveling waves' wavefronts is considered as corner points in digital image of waveshape. The corner points can be extracted precisely by Harris corner detector, and both false corner points and non-fault caused disturbance can be eliminated according to the calculated distance between two neighbour corner points and the angle of the corner point. The proposed method is proved feasible and effective by digital simulated test.


2006 ◽  
Vol 23 (3-4) ◽  
pp. 503-507 ◽  
Author(s):  
I.J. MURRAY ◽  
N.R.A. PARRY ◽  
D.J. McKEEFRY

Changes of color perception in the peripheral field are measured using an asymmetric simultaneous matching paradigm. The data confirm previous observations in that saturation changes can be neutralized if the test target is increased in size. However, this compensation does not apply to hue shifts. We show that some hues remain unchanged with eccentricity whereas others exhibit substantial changes. Here the color shifts are plotted in terms of a second-stage cone opponent model. The data suggest that the S-L+M channel is more robust to increasing eccentricity than the L-M channel. Observations are interpreted in terms of the known underlying morphological and physiological differences in these channels.


Author(s):  
D.J Needham ◽  
J Billingham

In this paper, we develop a theory based on local asymptotic coordinate expansions for the unsteady propagation of a corner point on the constant-pressure free surface bounding an incompressible inviscid fluid in irrotational motion under the action of gravity. This generalizes the result of Stokes and Michell relating to the horizontal propagation of a corner at constant speed.


2021 ◽  
Vol 5 (6) ◽  
pp. 1036-1043
Author(s):  
Ardi wijaya ◽  
Puji Rahayu ◽  
Rozali Toyib

Problems in image processing to obtain the best smile are strongly influenced by the quality, background, position, and lighting, so it is very necessary to have an analysis by utilizing existing image processing algorithms to get a system that can make the best smile selection, then the Shi-Tomasi Algorithm is used. the algorithm that is commonly used to detect the corners of the smile region in facial images. The Shi-Tomasi angle calculation processes the image effectively from a target image in the edge detection ballistic test, then a corner point check is carried out on the estimation of translational parameters with a recreation test on the translational component to identify the cause of damage to the image, it is necessary to find the edge points to identify objects with remove noise in the image. The results of the test with the shi-Tomasi algorithm were used to detect a good smile from 20 samples of human facial images with each sample having 5 different smile images, with test data totaling 100 smile images, the success of the Shi-Tomasi Algorithm in detecting a good smile reached an accuracy value of 95% using the Confusion Matrix, Precision, Recall and Accuracy Methods.


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