scholarly journals Abstraction of Unclear Weld Defect Images from X-ray Film by Background Subtraction Method and Region Growing Method.

1999 ◽  
Vol 65 (634) ◽  
pp. 2561-2567 ◽  
Author(s):  
Kimiya AOKI ◽  
Yuuki YOSHIDA ◽  
Yasuo SUGA
Keyword(s):  
Background Subtraction ◽  
Region Growing ◽  
Subtraction Method ◽  
X Ray ◽  
Weld Defect

Research on FAE Cloud Image Processing Method Based on Background Subtraction and Region Growing

2018 ◽  
Vol 32 (07) ◽  
pp. 1854019
Author(s):  
Fang Wang ◽  
Yi-Zhao Li ◽  
Li-Ping Li ◽  
De-Ren Kong
Keyword(s):  
Image Processing ◽  
High Precision ◽  
Background Subtraction ◽  
Region Growing ◽  
Processing Method ◽  
Geometric Parameters ◽  
Subtraction Method ◽  
Image Processing Method ◽  
Integrate Area

After the first initiation, the Fuel Air Explosive (FAE) cloud formed through fuel explosion dispersal and it will generate tremendous damaging power after being detonated the second time. As the damaging power is closely related to the determination of reinitiation time, it is of great significance to study the growth principle of FAE cloud by means of analyzing FAE cloud images. Combining with background subtraction and region growing, an improved region growing image processing method was proposed, in which the seeds of region growing abstracted through background subtraction method and the growing criterion was modified. With this method, the integrate area of cloud can be obtained for extracting geometric parameters. Experiments were carried out on both cloudy and sunny days, and image overlap score was used to quantitatively evaluate the accuracy of images segmentation. The result indicated that this image processing method has advantages of high precision and robustness. In addition, the computation burden is reduced significantly compared with traditional region growing method.

An Improved Spectral Background Subtraction Method Based on Wavelet Energy

2016 ◽  
Vol 70 (12) ◽  
pp. 1994-2004 ◽  
Author(s):  
Fengkui Zhao ◽  
Jian Wang ◽  
Aimin Wang
Keyword(s):  
Background Subtraction ◽  
Experimental Spectrum ◽  
Estimation Algorithm ◽  
Simulated Spectrum ◽  
Subtraction Method ◽  
X Ray ◽  
Background Estimation ◽  
Wavelet Energy ◽  
Entropy Principle ◽  
The Difference

Most spectral background subtraction methods rely on the difference in frequency response of background compared with characteristic peaks. It is difficult to extract accurately the background components from the spectrum when characteristic peaks and background have overlaps in frequency domain. An improved background estimation algorithm based on iterative wavelet transform (IWT) is presented. The wavelet entropy principle is used to select the best wavelet basis. A criterion based on wavelet energy theory to determine the optimal iteration times is proposed. The case of energy dispersive X-ray spectroscopy is discussed for illustration. A simulated spectrum with a prior known background and an experimental spectrum are tested. The processing results of the simulated spectrum is compared with non-IWT and it demonstrates the superiority of the IWT. It has great significance to improve the accuracy for spectral analysis.

scholarly journals Background subtraction for fluorescence EXAFS data of a very dilute dopantZinZ + 1 host

2011 ◽  
Vol 18 (4) ◽  
pp. 679-680 ◽  
Author(s):  
Scott Medling ◽  
Frank Bridges
Keyword(s):  
Background Subtraction ◽  
Raman Peak ◽  
Exafs Data ◽  
X Ray ◽  
Fluorescence Peak ◽  
Large Background

When conducting EXAFS at the CuK-edge for ZnS:Cu with very low Cu concentration (<0.04% Cu), a large background was present that increased with energy. This background arises from a Zn X-ray Raman peak, which moves through the Cu fluorescence window, plus the tail of the Zn fluorescence peak. This large background distorts the EXAFS and must be removed separately before reducing the data. A simple means to remove this background is described.

Generation of a 3D model of the inside volume of shoes for e-commerce applications using industrial X-ray computed tomography

2021 ◽  
Author(s):  
J Wittmann ◽  
G Herl ◽  
J Hiller
Keyword(s):  
Computed Tomography ◽  
3D Model ◽  
Region Growing ◽  
Surface Model ◽  
Economic Potential ◽  
X Ray ◽  
Internet Users ◽  
Surface Data ◽  
X Ray Computed ◽  
The Individual

Abstract In 2018, 47 % of global internet users had purchased footwear products through the internet, making it the second most popular online shopping category worldwide right after clothing with 57 %. In the same year, on average, about every sixth parcel delivered in Germany (16.3 %) was returned. With the effort and costs that are associated with the return of shoes, the objective of reducing the number of returns for shoes promises an enormous economic potential and helps to reduce the CO2 emissions due to a lower trafic volume. This paper presents a workflow for determining the inside volume surface of shoes using industrial X-ray computed tomography (CT). The fundamental idea is based on the Region Growing (RG) method for the segmentation of the shoe's inner volume. Experiments are performed to illustrate the correlation of image quality and segmentation result. After obtaining the 3D surface model of an individual foot, the inner volume surface data of a scanned shoe can then be registered and evaluated in order to provide a reliable feedback for the customer regarding the accuracy of fit of a shoe and the individual foot on the basis of an overall "metric of comfort" before buying online. This step is not part of the work at hand. Conclusions are drawn and suggestions for improving the robustness and the exibility of the workflow are given, so it can be adapted to various shoe types and implemented in a fully automated measurement process in the future.

A novel background subtraction method based on color invariants

2013 ◽  
Vol 117 (11) ◽  
pp. 1589-1597 ◽  
Author(s):  
Hong Zhou ◽  
Yiru Chen ◽  
Rong Feng
Keyword(s):  
Background Subtraction ◽  
Subtraction Method
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