scholarly journals Increasing reliability of forensic analysis while research on destroyed relief marking with magneto-optical devices

2021 ◽  
Vol 23 (1) ◽  
pp. 148-166
Author(s):  
Yu. Agalidi ◽  
O. Koshel
Keyword(s):  
Optical Imaging ◽  
Signal To Noise Ratio ◽  
Forensic Analysis ◽  
Imaging Method ◽  
Signal Recognition ◽  
Visualization Method ◽  
Signal To Noise ◽  
Instrumental Data ◽  
Noise Ratio ◽  
Correct Signal

While research on destroyed relief marking of metal objects using the magneto-optical method, visualization of (invisible) fields of internal stress in the VIN plate area is performed and then a forensic analysis of obtained instrumental data is carried out (indirect organoleptic observation of the visualization results); thus, forensic analysis reliability of results directly depends on sensitivity of instruments and informativeness of instrumental data. The main quantitative characteristic in this case is probability of correct signal recognition  (contours of marking signs) against the background of noise (structural noise of investigated surface and the noise of the visualization method itself) determined by the signal-to-noise ratio. This article presents results of a comparative experimental assessment of signal-to-noise ratio and probability of correct signal recognition while restoringthe destroyed relief markings for two complexes of magneto-optical imaging – models of 2006 and 2018. This article purpose is a quantitative and qualitative comparative assessment of results of visualization of internal stresses in areas of completely removed relief marking of metal objects. The results of successful practical research obtained by forensic experts from different countries make it possible to assess effectiveness and prospects of using the magneto-optical imaging method. In a new modification of the magneto-optical complex: signal level is 4.35 dB higher (contrast of reconstructed marking signs); 2.71 dB lower noise level (surface relief/texture and magnetic copying noise);• probability of correct character recognition is P> 0.995 (increased by 14.9%). Technical improvements in implementation of magneto-optical visualization method made it possible to expand the range of materials for research objects(magnetic and electrically conductive materials were investigated). The high efficiency of method for restoring marking is illustrated by results of forensic examinations for materials with a low level of residual stresses (aluminum alloy, low-carbon steel) which  chemical etching method did not give results for. The use of new modification allows examining the rust layer, up to cases of corrosion to the entire depth of marks. Considering non-destructive nature of magneto-optical researches, possibility of their repeated repetition without losing  object properties, this method (in accordance with the order of application of types of studies) deserves more attention for application.

scholarly journals Low-latency time-of-flight non-line-of-sight imaging at 5 frames per second

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ji Hyun Nam ◽  
Eric Brandt ◽  
Sebastian Bauer ◽  
Xiaochun Liu ◽  
Marco Renna ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Time Of Flight ◽  
Motion Blur ◽  
Line Of Sight ◽  
Low Latency ◽  
Imaging Method ◽  
Signal To Noise ◽  
Array Detectors ◽  
Noise Ratio ◽  
Non Line Of Sight

AbstractNon-Line-Of-Sight (NLOS) imaging aims at recovering the 3D geometry of objects that are hidden from the direct line of sight. One major challenge with this technique is the weak available multibounce signal limiting scene size, capture speed, and reconstruction quality. To overcome this obstacle, we introduce a multipixel time-of-flight non-line-of-sight imaging method combining specifically designed Single Photon Avalanche Diode (SPAD) array detectors with a fast reconstruction algorithm that captures and reconstructs live low-latency videos of non-line-of-sight scenes with natural non-retroreflective objects. We develop a model of the signal-to-noise-ratio of non-line-of-sight imaging and use it to devise a method that reconstructs the scene such that signal-to-noise-ratio, motion blur, angular resolution, and depth resolution are all independent of scene depth suggesting that reconstruction of very large scenes may be possible.

Signal-to-Noise Ratio Analysis of Dual-Channel Shearing Interferometry Hyperspectral Imaging Method

2018 ◽  
Vol 38 (5) ◽  
pp. 0511001
Author(s):  
刘成淼 Liu Chengmiao ◽  
李建欣 Li Jianxin ◽  
朱日宏 Zhu Rihong ◽  
崔向群 Cui Xiangqun
Keyword(s):  
Hyperspectral Imaging ◽  
Signal To Noise Ratio ◽  
Imaging Method ◽  
Ratio Analysis ◽  
Signal To Noise ◽  
Shearing Interferometry ◽  
Dual Channel ◽  
Noise Ratio

Fast 2D super resolution ISAR imaging method under low signal‐to‐noise ratio

2017 ◽  
Vol 11 (10) ◽  
pp. 1495-1504 ◽  
Author(s):  
Shaodong Li ◽  
Wenfeng Chen ◽  
Weijian Liu ◽  
Jun Yang ◽  
Xiaoyan Ma
Keyword(s):  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Imaging Method ◽  
Signal To Noise ◽  
Isar Imaging ◽  
Noise Ratio

scholarly journals Quantification of Optical Images of Cortical Responses for Inferring Functional Maps

2009 ◽  
Vol 101 (5) ◽  
pp. 2708-2724 ◽  
Author(s):  
Gopathy Purushothaman ◽  
Ilya Khaytin ◽  
Vivien A. Casagrande
Keyword(s):  
Optical Imaging ◽  
Quantitative Methods ◽  
Functional Organization ◽  
Signal To Noise Ratio ◽  
Temporal Frequency ◽  
Signal To Noise ◽  
Probability Maps ◽  
Optical Images ◽  
Good Spatial Resolution ◽  
Noise Ratio

Optical imaging of cortical signals enables the mapping of functional organization across large patches of cortex with good spatial resolution. But techniques for the quantitative analysis and interpretation of these images are limited. Frequently the functional architecture of the cortex is inferred from the visible topography of cortical reflectance images averaged or differenced across stimulus conditions and scaled or color-coded for presentation. Such qualitative assessments have sometimes led to divergent conclusions particularly about the organization of spatial and temporal frequency preferences in the primary visual cortex. We applied quantitative methods derived from signal detection theory to objectively interpret optical images. The differential response to any two arbitrary stimuli was represented at each pixel as the probability of discriminating between the two stimuli given the reflectance values at that pixel. These probability maps reduced false alarms and provided better signal-to-noise ratio in fewer trials than difference maps. We applied these methods to optical images of primate primary visual area (V1) obtained in response to sinusoidal gratings of different orientations and spatiotemporal frequencies. Clustering by orientation preference was stronger than that for spatial frequency, whereas clustering by temporal frequency preference was the weakest, largely in agreement with a previous electrophysiological study that quantified the degree of clustering of neurons for various response properties using uniform, quantitative criterion. We suggest that probability maps can extend the applicability of optical imaging to investigations of finer aspects of cortical functional organization through better signal-to-noise ratio and uniform, quantitative criteria for interpretation.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

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