%0 Generic
%A Fernhout, Merit
%D 2023
%T Annotated images of microscopy images from carbon fibre composites
%U 
%R 10.4121/bf11171a-1f57-4a8a-9768-757850d13665.v1
%K annotation
%K semantic segmentation
%K machine learning
%K images
%K fibres
%K voids
%K composites
%K carbon fibre
%X <p>Four data sets containing 500, 500, 1000 and 32 images of 256 x 256 pixels of parts of microscopy images of cross sections of carbon fibre composite laminates. The data sets contain corresponding annotated masks for every image. Each pixel is either annotated in the classes: matrix material, fibre or void and is respectively labelled with 0, 1 and 2. The masks are made by locating the centres of the fibres with a find local maxima method in ImageJ. These locations are then used to draw perfect circles with the average fibre radius around them to indicate the fibres. The voids are detected using a thresholding algorithm based on a minimum method. The data sets can be used to train, validate and test semantic segmentation algorithms.</p><p></p><p></p>
%I 4TU.ResearchData