Fatigue Testing of High-density Polyethylene and Polycarbonate with Crack Length Measurement Using Image Processing Techniques

1994 ◽  
Vol 22 (5) ◽  
pp. 410 ◽  
Author(s):  
DR Petersen ◽  
AC Riemslag
Keyword(s):  
Image Processing ◽  
Crack Length ◽  
High Density Polyethylene ◽  
Fatigue Testing ◽  
High Density ◽  
Length Measurement ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Crack Length Measurement

Automatic Crack Length Measurement of Concrete Structure Based on Image Processing

2014 ◽  
Vol 1030-1032 ◽  
pp. 728-731 ◽  
Author(s):  
Qi Zi Huang Peng ◽  
Wen Wei Huang ◽  
Ying Lu
Keyword(s):  
Image Processing ◽  
Crack Length ◽  
Concrete Structure ◽  
Concrete Surface ◽  
Length Measurement ◽  
Inspection System ◽  
Time Varying ◽  
Structural Surface ◽  
The Stability ◽  
Crack Length Measurement

The safety of concrete structure can be evaluated by manual survey through the visible crack shown on structural surface, but the manual survey is costly and time-consuming. To improve this, a novel image-based crack length measurement is proposed. The method starts with getting time varying crack images by proposed inspection system. Then retrieve crack skeleton from crack images by pre-processing, and construct crack skeleton of tree structure. After getting crack trunk by pruning small edges from crack skeleton, the length of crack is figure out. This method can measure crack length automatically, which will make contribution to enhance the stability, durability and safety of concrete structure. The validity and accuracy of the proposed method was tested by an experiment using images of a real concrete surface.

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.

Rice Panicle Blast Detection and Grading Based on Image Processing Techniques

2019 ◽  
Vol 7 (5) ◽  
pp. 165-168 ◽  
Author(s):  
Prabira Kumar Sethy ◽  
Swaraj Kumar Sahu ◽  
Nalini Kanta Barpanda ◽  
Amiya Kumar Rath
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Panicle Blast ◽  
Processing Techniques

Identification of Cucumber Leaf Disease using Image Processing Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 1493-1499
Author(s):  
Shrutika.C.Rampure . ◽  
Dr. Vindhya .P. Malagi ◽  
Dr. Ramesh Babu D.R
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Leaf Disease ◽  
Processing Techniques

Tensile strength of clayey soil and the strain analysis based on image processing techniques

2019 ◽  
Vol 253 ◽  
pp. 137-148 ◽  
Author(s):  
Hao-Da Li ◽  
Chao-Sheng Tang ◽  
Qing Cheng ◽  
Sheng-Jie Li ◽  
Xue-Peng Gong ◽  
...  
Keyword(s):  
Image Processing ◽  
Tensile Strength ◽  
Clayey Soil ◽  
Strain Analysis ◽  
Image Processing Techniques ◽  
Processing Techniques
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