Title :
Materials discovery: Fine-grained classification of X-ray scattering images
Author :
Kiapour, Mohammad Hadi ; Yager, Kevin ; Berg, Alexander C. ; Berg, Tamara
Author_Institution :
Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Abstract :
We explore the use of computer vision methods for organizing, searching, and classifying x-ray scattering images. X-ray scattering is a technique that shines an intense beam of x-rays through a sample of interest. By recording the intensity of x-ray deflection as a function of angle, scientists can measure the structure of materials at the molecular and nano-scale. Current and planned synchrotron instruments are producing x-ray scattering data at an unprecedented rate, making the design of automatic analysis techniques crucial for future research. In this paper, we devise an attribute-based approach to recognition in x-ray scattering images and demonstrate applications to image annotation and retrieval.
Keywords :
X-ray imaging; image classification; image retrieval; materials science computing; X-ray deflection; X-ray scattering image classification; X-ray scattering image organization; X-ray scattering image recognition; X-ray scattering image searching; X-ray scattering images; attribute-based approach; computer vision methods; fine-grained classification; image annotation; image retrieval; materials discovery; Computer vision; Instruments; Materials; Scattering; Semiconductor device measurement; X-ray imaging; X-ray scattering;
Conference_Titel :
Applications of Computer Vision (WACV), 2014 IEEE Winter Conference on
Conference_Location :
Steamboat Springs, CO
DOI :
10.1109/WACV.2014.6836004