Speckle tracking approaches in speckle correlation sensing

<div>Data and code used to generate the conference paper:</div><div><br></div><div>"Speckle tracking approaches in speckle correlation sensing"</div><div>Thomas O. H. Charrett, Krzysztof Kotowski, and Ralph P. Tatam </div><div>SPIE Optics and Optoelectonics, Prague, 2017.</div><div><br></div><div><br></div><div>Files:</div><div>------</div><div><br></div><div>lib_feature_tracking.py - python module/library used to simplify the other scripts</div><div><br></div><div>feature detectors.py - python script used to test processing times of feature detectors.</div><div><br></div><div>feature descriptors.py - python script used to test processing times of feature descriptors and matching methods</div><div><br></div><div>modelled shifts.py - python script used to generate figure 1 - accuracy assesment.</div><div><br></div><div>experimental shifts.py - python script used to compare feature tracking method with cross correlation using real data (figure 2)</div><div><br></div><div>experimental rotations.py - python script used to test rotation performance using experimental data. Used to generate figure 3.</div><div> </div><div>random positions.npy - 100 x (512,512) independent speckle patterns in numpy binary format. Used for table 1, table 2 and figure 1</div><div><br></div><div>linear move direction=0.0 speed=5.0mms-1.npy - 100 x (512,512) speckle patterns recorded using a speckle velocimetry sensor on XY stages travelling at 5mm/s in the y-direction. In numpy binary format.Used for figure 2.</div><div><br></div><div>z rotation.npy - 721 x (512,512) speckle patterns for angles 0 to 360.0 degrees in 0.5 degree steps. Used for figure 3.</div><div><br></div><div>Comments:</div><div>----------------</div><div>OpenCV version: 3.1.0</div><div><br></div><div>Numpy python library available at http://www.numpy.org/.</div><div>Numpy version: 1.10.2</div><div><br></div><div>Load numpy binary format using:</div><div><br></div><div>>>> import numpy as np</div><div>>>> imgs = np.load( filename )</div><div><br></div>