A new test method and a measurement system was proposed and developed to evaluate the bending and twisting properties of textile fabrics. The measurement system and the test method is based on the mechanical device, sensors and microelectronics and simulates the dynamic process during the fabric is bent and twisted. The virtual instrument based system can measure the dynamic changes of the signals due to the bending and twisting loads. Derived from the test data, a series of indices are defined to characterize the bending and twisting properties. The test and evaluation method, the experiments and the test results are reported. The analysis of the variance for intra-laboratory test was performed to determine the precisions of the test method and the measurement system. The measurement system provides a method for objective measurement and evaluation of bending and twisting properties of textile fabrics.
A new approach of multi-modal medical image registration is proposed to overcome the drawbacks of mutual
information as taking no consideration of the space information, taking all intensities without distinction, and being
sensitive to noise. The proposed method firstly extracts the phase congruencies of the reference and floating image,
secondly, it computes quantitative-qualitative mutual information with the phase congruency mappings, finally, the
geometric transform is optimized by Particle Swarm Optimization. The quantitative-qualitative mutual information used
in our algorithm select the pixels whose utility are larger than the threshold of 1. In addition, Mutual information
incorporating phase congruency assimilates the information of both intensity and space. Experiment results show that our
approach is more robust in suppressing noise and can achieve higher accuracy.
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