Natural-textured-object recognition using spatial matched filtering technique

1993 ◽  
Author(s):  
K. M. Vinogradov ◽  
A. B. Zmicherevski ◽  
N. V. Kovalenkova ◽  
Alexandre V. Lukin
Keyword(s):  
Object Recognition ◽  
Matched Filtering ◽  
Filtering Technique

scholarly journals Extraction of Blood Vessels in Retinal Images Using Four Different Techniques

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Asloob Ahmad Mudassar ◽  
Saira Butt
Keyword(s):  
Blood Vessel ◽  
Cross Sections ◽  
Retinal Images ◽  
Matched Filtering ◽  
Edge Enhancement ◽  
Promising Technique ◽  
Filtering Technique ◽  
Continuation Algorithm ◽  
Line Cross ◽  
Vessel Extraction

A variety of blood vessel extraction (BVE) techniques exist in the literature, but they do not always lead to acceptable solutions especially in the presence of anomalies where the reported work is limited. Four techniques are presented for BVE: (1) BVE using Image Line Cross-Sections (ILCS), (2) BVE using Edge Enhancement and Edge Detection (EEED), (3) BVE using Modified Matched Filtering (MMF), and (4) BVE using Continuation Algorithm (CA). These four techniques have been designed especially for abnormal retinal images containing low vessel contrasts, drusen, exudates, and other artifacts. The four techniques were applied to 30 abnormal retinal images, and the success rate was found to be (95 to 99%) for CA, (88–91%) for EEED, (80–85%) for MMF, and (74–78%) for ILCS. Application of these four techniques to 105 normal retinal images gave improved results: (99-100%) for CA, (96–98%) for EEED, (94-95%) for MMF, and (88–93%) for ILCS. Investigations revealed that the four techniques in the order of increasing performance could be arranged as ILCS, MMF, EEED, and CA. Here we demonstrate these four techniques for abnormal retinal images only. ILCS, EEED, and CA are novel additions whereas MMF is an improved and modified version of an existing matched filtering technique. CA is a promising technique.

Noise filtering techniques for Lamb waves in structural health monitoring

2018 ◽  
Vol 14 (4) ◽  
pp. 676-694
Author(s):  
Ambuj Sharma ◽  
Sandeep Kumar ◽  
Amit Tyagi
Keyword(s):  
Crack Detection ◽  
Lamb Waves ◽  
Random Noise ◽  
Matched Filtering ◽  
Noise Filtering ◽  
Content Type ◽  
Time Frequency ◽  
Structural Health ◽  
Filtering Technique ◽  
Filtering Techniques

Purpose The real challenges in online crack detection testing based on guided waves are random noise as well as narrow-band coherent noise; and to achieve efficient structural health assessment methodology, magnificent extraction of noise and analysis of the signals are essential. The purpose of this paper is to provide optimal noise filtering technique for Lamb waves in the diagnosis of structural singularities. Design/methodology/approach Filtration of time-frequency information of guided elastic waves through the noisy signal is investigated in the present analysis using matched filtering technique which “sniffs” the signal buried in noise and most favorable mother wavelet based denoising methods. The optimal wavelet function is selected using Shannon’s entropy criterion and verified by the analysis of root mean square error of the filtered signal. Findings Wavelet matched filter method, a newly developed filtering technique in this work and which is a combination of the wavelet transform and matched filtering method, significantly improves the accuracy of the filtered signal and identifies relatively small damage, especially in enormously noisy data. A comparative study is also performed using the statistical tool to know acceptability and practicability of filtered signals for guided wave application. Practical implications The proposed filtering techniques can be utilized in online monitoring of civil and mechanical structures. The algorithm of the method is easy to implement and found to be successful in accurately detecting damage. Originality/value Although many techniques have been developed over the past several years to suppress random noise in Lamb wave signal but filtration of interferences of wave modes and boundary reflection is not in a much matured stage and thus needs further investigation. The present study contains detailed information about various noise filtering methods, newly developed filtration technique and their efficacy in handling the above mentioned issues.

scholarly journals Prospects of detection of the first sources with SKA using matched filters

2017 ◽  
Vol 12 (S333) ◽  
pp. 122-125
Author(s):  
Raghunath Ghara ◽  
T. Roy Choudhury ◽  
Kanan K. Datta ◽  
Garrelt Mellema ◽  
Samir Choudhuri ◽  
...  
Keyword(s):  
Parameter Space ◽  
Efficient Method ◽  
Field Of View ◽  
Matched Filtering ◽  
Mcmc Algorithm ◽  
Matched Filters ◽  
Dimensional Parameter ◽  
Filtering Technique ◽  
Blind Search

AbstractThe matched filtering technique is an efficient method to detect H ii bubbles and absorption regions in radio interferometric observations of the redshifted 21-cm signal from the epoch of reionization and the Cosmic Dawn. Here, we present an implementation of this technique to the upcoming observations such as the SKA1-low for a blind search of absorption regions at the Cosmic Dawn. The pipeline explores four dimensional parameter space on the simulated mock visibilities using a MCMC algorithm. The framework is able to efficiently determine the positions and sizes of the absorption/H ii regions in the field of view.

scholarly journals Efficient Detection of Multiple FBG Wavelength Peaks using Matched Filtering Technique

2021 ◽  
Author(s):  
Sunil Kumar
Keyword(s):  
Cross Correlation ◽  
Reference Signal ◽  
Peak Detection ◽  
Matched Filtering ◽  
Peak Wavelength ◽  
Zero Crossing ◽  
Efficient Detection ◽  
Spectral Signal ◽  
Filtering Technique ◽  
The Cross

Abstract We propose an efficient technique for FBG peak detection based on matched filtering technique. The matched filtering process is based on resonance point estimation between a standard reference spectral signal and a reflected spectrum of FBG. The desired peak wavelength and corresponding peak intensity are predicted by determining of the cross-correlation between the FBG signal and 3rd derivative of the reference signal. The peak wavelength and intensity are found from the zero-crossing points of the cross-correlation function. The Mexican-hat wavelet function is chosen as the reference spectral signal due to its narrow shape. The proposed algorithm can suitably be used for multiple peak detection when several FBGs are cascaded and if the FBG signal is weak and noisy.

Three-dimensional object recognition from digital Fresnel hologram by wavelet matched filtering

2006 ◽  
Vol 259 (2) ◽  
pp. 499-506 ◽  
Author(s):  
Anith Nelleri ◽  
Unnikrishnan Gopinathan ◽  
Joby Joseph ◽  
Kehar Singh
Keyword(s):  
Object Recognition ◽  
Three Dimensional ◽  
Matched Filtering ◽  
Dimensional Object ◽  
Fresnel Hologram

Use It and Still Lose It?

GeroPsych ◽  
2010 ◽  
Vol 23 (3) ◽  
pp. 169-175 ◽  
Author(s):  
Adrian Schwaninger ◽  
Diana Hardmeier ◽  
Judith Riegelnig ◽  
Mike Martin
Keyword(s):  
Object Recognition ◽  
Cognitive Development ◽  
Recognition Test ◽  
Cognitive Aging ◽  
Recognition Task ◽  
Airport Security ◽  
Visual Object ◽  
Long Term Effects ◽  
Object Recognition Test ◽  
X Ray

In recent years, research on cognitive aging increasingly has focused on the cognitive development across middle adulthood. However, little is still known about the long-term effects of intensive job-specific training of fluid intellectual abilities. In this study we examined the effects of age- and job-specific practice of cognitive abilities on detection performance in airport security x-ray screening. In Experiment 1 (N = 308; 24–65 years), we examined performance in the X-ray Object Recognition Test (ORT), a speeded visual object recognition task in which participants have to find dangerous items in x-ray images of passenger bags; and in Experiment 2 (N = 155; 20–61 years) in an on-the-job object recognition test frequently used in baggage screening. Results from both experiments show high performance in older adults and significant negative age correlations that cannot be overcome by more years of job-specific experience. We discuss the implications of our findings for theories of lifespan cognitive development and training concepts.

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