Comparing image processing techniques for asphalt concrete X-ray CT images

2014 ◽  
pp. 565-574
Author(s):  
Stefan Oprea ◽  
Costin Marinescu ◽  
Ioan Lita ◽  
Mariana Jurianu ◽  
Daniel Alexandru Visan ◽  
...  

1995 ◽  
Author(s):  
Lawrence M. Jordan ◽  
Li Gao ◽  
Peter G. Davis ◽  
Frank A. DiBianca ◽  
Jeno I. Sebes ◽  
...  

Author(s):  
Folasade Olubusola Isinkaye ◽  
Abiodun Gabriel Aluko ◽  
Olayinka Ayodele Jongbo

2018 ◽  
Vol 89 (15) ◽  
pp. 3007-3023 ◽  
Author(s):  
Noman Haleem ◽  
Xin Liu ◽  
Christopher Hurren ◽  
Stuart Gordon ◽  
Saeed S Najar ◽  
...  

The micro-level structure of staple yarn and the fiber arrangement inside it has a decisive influence on its physical properties. This study aims to introduce a combined method based on micro computerized tomography (micro CT) and digital image processing techniques to probe the ring yarn structure in a non-invasive manner. Two micro CT systems at different CT settings were applied to achieve optimal quality CT images of cotton ring yarns. Three image processing algorithms were proposed to enhance and process the yarn CT images in order to extract yarn structural information. The proposed method was also applied on two yarn specimens, which varied significantly in terms of their tensile strength, to study differences in their underlying structures. The results showed that the longitudinal arrangement of fibers in terms of their migratory behavior had a decisive influence on the tensile properties of the yarn. The stronger yarn showed a higher value of the amplitude and intensity of fiber migration compared to the weaker yarn, suggesting that the protocol established in this study can effectively reveal fiber arrangements within a staple yarn structure in a non-invasive manner.


Image processing in biomedical field is being increasingly used for the detection and diagnosis of various abnormalities in the body parts. The detection of brain tumours using image processing on MRI images is one such field where better results are obtained as comparative to CT-scan and x-ray. Prior detection of the brain tumour is desirable and possible with the help of machine learning and image processing techniques. These techniques detect even a small abnormality in the human brain following a four-stage process which includes pre-processing, segmentation, feature extraction and optimization. Different parameters such as accuracy, PSNR, MSE are calculated to find out the efficiency of process and to compare it with other methods. This paper reviews about various different approaches which are used to detect the brain tumor using image processing techniques.


Sign in / Sign up

Export Citation Format

Share Document