Photometric stereo data of non-crimp fabric boundaries

<p><strong>DATA DESCRIPTION</strong></p> <p>This data set was acquired in the context of EU project ZAero. This project has received funding from the European Union&rsquo;s Horizon 2020 research and innovation programme under grant agreement No 721362. Project duration: 2016/10/01 - 2019/09/30. This data set contains a set of 68 HDF5 files from two different example surface patches of NCF carbon fiber fabrics.</p> <p>For more information about the HDF5 format, please visit the HDF5 Group website:<br> https://www.hdfgroup.org/solutions/hdf5/</p> <p>Each file contains data from a photometric stereo vision system [1]. The data set is intended for evaluation of methods for carbon fiber fabric edge detection [2].</p> <p>Each file contains a single 3-dimensional (W x H x L) array &#39;raw&#39; with:<br> H...height of the images<br> W...width of the images<br> L...number of images with different light sources (L = 8)</p> <p>An example for loading and visualizing the data in Python comes with this data set:<br> readDataExample.py</p> <p><br> <strong>REFERENCES</strong></p> <p>[1]<br> @inproceedings{Palfinger2011, &nbsp;<br> &nbsp; author&nbsp;&nbsp;&nbsp; = {Palfinger, Werner and Thumfart, Stefan and Eitzinger, Christian},<br> &nbsp; title&nbsp;&nbsp;&nbsp;&nbsp; = {Photometric stereo on carbon fiber surfaces},<br> &nbsp; booktitle = {35th Workshop of the Austrian Association for Pattern Recognition},<br> &nbsp; year&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; = {2011}<br> }</p> <p>[2]<br> @inproceedings{Zambal2019,<br> &nbsp; author&nbsp;&nbsp;&nbsp; = {Zambal, Sebastian and Heindl, Christoph and Eitzinger, Christian}<br> &nbsp; title&nbsp;&nbsp;&nbsp;&nbsp; = {Probabilistic Modelling combined with a CNN for boundary detection of carbon fiber fabrics},<br> &nbsp; booktitle = {IEEE International Conference on Industrial Informatics (INDIN)}<br> &nbsp; year&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; = {2019}<br> }</p> <p>&nbsp;</p> <p>&nbsp;</p>