Abstract
In recent years, high elongation materials are widely used. Therefore, it is important to investigate the tensile properties of high elongation materials for engineering applications. Video extensometer is equipment for measuring the materials’ tensile properties. It uses image processing technology to match data points and measures the actual deformation. However, when measuring high elongation materials, motion blur will appear on the collected images, which can affect the accuracy of image matching. In this paper, we proposed an image matching method which is based on Local Phase Quantization (LPQ) features to reduce the interference of the motion blur and improve the accuracy of the image matching algorithms as well. The experimental results on simulations show that the proposed initialization method is sufficiently accurate to enable the correct convergence of the subsequent optimization in the presence of motion blur. The experiment of uniaxial tensile also verifies the accuracy and robustness of the method.
Highlights
High elongation materials are an important class of materials for structural applications such as transportation, civil infrastructures, and biomedical applications
We proposed an image matching method which is based on Local Phase Quantization (LPQ) features to reduce the interference of the motion blur and improve the accuracy of the image matching algorithms as well
For the high elongation materials, the mechanical extensometer which is mounted directly onto the material via blade causes many problems such as the following: (1) mutual friction will reduce the measurement accuracy; (2) the total deformation cannot be measured in the uniaxial tensile test; (3) the measuring range is limited
Summary
High elongation materials are an important class of materials for structural applications such as transportation, civil infrastructures, and biomedical applications. Reference [4] proposes an off-axis digital image correlation method for real-time, noncontact, and targetless measurement of vertical deflection of bridges to achieve subpixel accuracy. Despite these advances, few works about eliminating extensometer’s measurement errors caused by motioninduced image blur to improve the accuracy have been reported. We will propose an image matching method for video extensometer to measure the parameters by utilizing Local Phase Quantization (LPQ) feature. This method is robust and performs well on images with serious motion blur and deformation.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
