I always make the same mistake again. Every time I learn about a strange working field for a theoretical scientist, I think now can nothing surprise me anymore. And then I find that: A paper which deals with algorithms for detecting and categorising the cracks (called craquelure) in paintings. Why? Craquelure are the result of age, material and environmental and physical impact. Understanding them can help to find better preserve-methods for paintings and can help in the authentication process. Therefore, many paintings are analysed using X-Rays. The X-Ray figures show the craquelure better than normal visual pictures. This is the point where algorithms are needed which can detect and simplify the cracks and sort them in categories using some measurable parameters. This is what is described in the paper from F.S. Abas and K. Martinez (2002). In the end, their algorithm can at least distinguish circular crack patterns from rectangular, spider-web, unidirectional and random patterns. Fun fact: The method they are using is adopted from the method for fingerprint detection. So let's summarise: There are scientists which create algorithms based on finger detection methods which help to sort crack patterns in X-Ray figures of paintings. I love this idea :) "Craquelure analysis for content-based retrieval."
F.S. Abas and K. Martinez. Digital Signal Processing, 2002. DSP 2002. 2002 14th International Conference on. Vol. 1. IEEE, 2002.
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IdeaI love to increase my general science knowledge by reading papers from different fields of science. Here I share some of them. Archiv
März 2018
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