scholarly journals Image Processing Algorithm for Quantitative Characterization of Thermal Imaging Acquired During On-line Weld Monitoring

2007 ◽  
Vol 1 (1) ◽  
pp. 36-40 ◽  
Author(s):  
N.M Nandhitha ◽  
N Manoharan ◽  
B Sheela Rani ◽  
B Venkatraman ◽  
P Kalyana Sundaram ◽  
...  
Keyword(s):  
Image Processing ◽  
Thermal Imaging ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Quantitative Characterization ◽  
On Line

Automatic macroscopic characterization of diesel sprays by means of a new image processing algorithm

2018 ◽  
Vol 29 (5) ◽  
pp. 055406 ◽  
Author(s):  
Guillermo Rubio-Gómez ◽  
S Martínez-Martínez ◽  
Luis F Rua-Mojica ◽  
Pablo Gómez-Gordo ◽  
Oscar A de la Garza
Keyword(s):  
Image Processing ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Diesel Sprays

scholarly journals Iterative feature detection of a coded checkerboard target for the geometric calibration of infrared cameras

2021 ◽  
Vol 10 (2) ◽  
pp. 207-218
Author(s):  
Sebastian Schramm ◽  
Jannik Ebert ◽  
Johannes Rangel ◽  
Robert Schmoll ◽  
Andreas Kroll
Keyword(s):  
Image Processing ◽  
Thermal Imaging ◽  
Feature Detection ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Image Information ◽  
Geometric Calibration ◽  
Circular Pattern ◽  
Infrared Cameras ◽  
Distortion Parameters

Abstract. The geometric calibration of cameras becomes necessary when images should be undistorted, geometric image information is needed or data from more than one camera have to be fused. This process is often done using a target with a checkerboard or circular pattern and a given geometry. In this work, a coded checkerboard target for thermal imaging cameras and the corresponding image processing algorithm for iterative feature detection are presented. It is shown that, due in particular to the resulting better feature detectability at image borders, lower uncertainties in the estimation of the distortion parameters are achieved.

Internal quality evaluation of chestnut using nuclear magnetic resonance

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Soo Hyun Park ◽  
Sang Ha Noh ◽  
Michael J. McCarthy ◽  
Seong Min Kim
Keyword(s):  
Image Processing ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Processing Algorithm ◽  
Internal Quality ◽  
Soluble Solid Content ◽  
Mr Images ◽  
Image Processing Algorithm ◽  
Internal Defects ◽  
Nuclear Magnetic

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.

Quantitative Characterization of Pore Arrangement in Pore Bands in Pressure Die Cast AZ91 Magnesium Alloy by Image Processing

2006 ◽  
Vol 514-516 ◽  
pp. 1477-1482 ◽  
Author(s):  
D. G. Leo Prakash ◽  
Doris Regener
Keyword(s):  
Image Processing ◽  
Magnesium Alloy ◽  
Programming Language ◽  
Az91 Magnesium Alloy ◽  
Quantitative Characterization ◽  
Processing Defect ◽  
Die Cast ◽  
Az91 Magnesium ◽  
Pore Arrangement

Microporosity is the major processing defect in pressure die cast AZ91 magnesium alloy. There is a big difference in the arrangement of pores in different regions of the castings. The present work explains the pore arrangement in pore bands and other regions. Quantification and characterization of pores in pore bands is expected to be useful to understand the process-propertymicrostructure correlation. A computational microstructural (image) analyzing technique has been developed by a programming language to quantify and analyze the micropores in pore bands. The pore band regions and the rest were separated and quantified. In addition, image analyzing technique was used to measure the clustering tendency of porosity in pore bands and it was compared with other regions.

An Image Processing Algorithm to Find New and Old Bruises

1995 ◽  
Vol 11 (5) ◽  
pp. 751-757 ◽  
Author(s):  
J. A. Throop ◽  
D. J. Aneshansley ◽  
B. L. Upchurch
Keyword(s):  
Image Processing ◽  
Processing Algorithm ◽  
Image Processing Algorithm
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