Computationally Intelligent Image Processing Techniques for Crack Detection in Structural Components from Imaged Data

2016 ◽  
Author(s):  
Daniel Gillaugh ◽  
Joseph A. Beck ◽  
Jeffrey M. Brown ◽  
Tommy George ◽  
Onome Scott-Emuakpor ◽  
...  
Keyword(s):  
Image Processing ◽  
Crack Detection ◽  
Structural Components ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Intelligent Image Processing

Crack Detection on Metal Surfaces Using Image Processing Techniques

2021 ◽  
Author(s):  
Megharaj Sonawane ◽  
Aditya Borse ◽  
Hrishikesh Sonawane ◽  
Aashish Mali ◽  
Prachi Rajarapollu
Keyword(s):  
Image Processing ◽  
Metal Surfaces ◽  
Crack Detection ◽  
Image Processing Techniques ◽  
Processing Techniques

Image Processing Techniques Applied to Automatic Measurement of the Fatigue-Crack

2005 ◽  
Vol 297-300 ◽  
pp. 34-39 ◽  
Author(s):  
Dae Hyun Ryu ◽  
Seung Hoon Nahm
Keyword(s):  
Image Processing ◽  
Fatigue Crack ◽  
Crack Detection ◽  
Residual Life ◽  
Detection System ◽  
Growth Behavior ◽  
Block Matching ◽  
Crack Growth Behavior ◽  
Image Processing Techniques ◽  
Processing Techniques

A crack detection system was developed to observe growth behavior of fatigue crack using the digital image processing techniques. The crack propagation behavior was observed successfully by combining block matching method and inclination threshold value method. The data obtained with this new system agreed with the existent data and the standard deviation was 0.03%. If the proposed method is utilized to develop a crack monitoring system to observe the crack growth behavior automatically, the time and effort needed for a fatigue test could be dramatically reduced. And also it will be easier to estimate and to manage efficiently the safety and residual life of industrial facilities.

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

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