This website houses a tool developed by the team at the Yale IPCH Lens Media Lab for the
use of characterizing texture data
taken from various samples of photographic paper. The tool primarily uses a characterization model known as the
Semi-Supervised Triplet Loss Neural Network for Asssessing Paper Texture Similarity, which was originally
developed within the ASPECT Lab at Western Washington University. The primary use for this tool is to create a
visual representation of a papers’ texture, which can range from smooth to rough, and with a wide degree of
variation in-between. This tool aims to identify and specify that in-between, and also match pre-loaded paper
textures in our database with potentially those uploaded by researchers. This tool will hopefully aid
conservators, researchers,
and scholars interested in the history of photography, to trace their texture profiles and develop new points of
understanding photographic paper collections.
click the image below to navigate to the texture toolbox
