Characterization of Yarn Mass Parameters and Production Characteristics Using Optical Sensors, Capacitive Sensors and Image Processing

2013 ◽  
Vol 2 (3) ◽  
pp. 145-156
Author(s):  
Vitor Carvalho ◽  
Nuno Goncalves ◽  
Filomena Soares ◽  
Rosa Vasconcelos ◽  
Michael Belsley
Keyword(s):  
Image Processing ◽  
Optical Sensors ◽  
Capacitive Sensors ◽  
Production Characteristics

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.

Improvement of Material Characterization of Curing Polymers by Image Processing

2002 ◽  
Vol 227 ◽  
pp. 205-210
Author(s):  
Victor Gonda ◽  
C.J. Liu ◽  
Cornelis van't Hof ◽  
Leo J. Ernst ◽  
G.Q. Zhang
Keyword(s):  
Image Processing ◽  
Material Characterization

IVUS Image Processing Methodologies

2013 ◽  
pp. 639-657
Author(s):  
Antonis A. Sakellarios ◽  
Christos V. Bourantas ◽  
Lambros S. Athanasiou ◽  
Dimitrios I. Fotiadis ◽  
Lampros K. Michalis
Keyword(s):  
Image Processing ◽  
Vessel Wall ◽  
Regions Of Interest ◽  
Manual Segmentation ◽  
Arterial Lumen ◽  
Ivus Image ◽  
Processing Techniques ◽  
Automated Methods

Intravascular Ultrasound (IVUS) is an invasive imaging technique that allows detailed visualization of the arterial lumen and outer vessel wall and permits characterization of the type of the plaque and quantification of its burden. Traditionally IVUS processing was performed manually. However, it became apparent that manual segmentation is time consuming, and the obtained results depend on the experience of the operators. To overcome these limitations and enhance the role of IVUS in clinical practice and research, several (semi-) automated methods have been developed that expedite detection of the regions of interest and/or characterization of the type of the plaque. In this chapter we review the available IVUS processing techniques and present the developed commercial solutions for IVUS segmentation and plaque characterization.

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