How can you enable people who are no longer able to write themselves to write a personal note or continue to write a diary in their own handwriting? A team of researchers at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) have now developed a method for imitating handwriting using artificial intelligence (AI). The more legible the writing, the easier it is to imitate.
In order to imitate handwriting using AI, the researchers led by Dr. Vincent Christlein, Chair of Computer Science 5 (Pattern Recognition), break writing down into individual steps.
The first step is known as skeletonisation, where the writing is reduced to a skeleton only one pixel wide. It is then transferred to an online sequence: like a digital signature on a tablet, a sequence like this includes temporal information, in other words when a stroke was made.
This information is then accumulated according to a determined schedule. The partial strokes in each line are identified and sorted from left to right according to their position. This is then followed by the writer style and image style transfer.
First of all, the programme creates a new word skeleton in the same style and reverses the skeletonisation, before information from the writing sample such as line width in the word or the colour of the writing is transferred and small errors corrected automatically, resulting in a homogeneous style of writing.
The team needs roughly five to seven paragraphs of the original writing sample to train the programme for new handwriting styles. Unlike other programmes which mimic handwriting, there is no need for interaction with the writer and it is not necessary to have a sample of all letters, as they can be derived using AI.
The results are comparatively good when it comes to imitating handwriting for individual words – in a study, test persons were unable to identify which handwritten text was produced by AI. Other computer-assisted procedures which are able to identify handwriting were also unable to differentiate the original from the imitation in some instances.
Dr. Christlein can imagine a variety of uses for the new procedure. It could help people who are physically not able to write themselves but would still like to write handwritten texts. Not only that, it could also be used to train programmes which can recognise historic writing.
Until now, this has required significant amounts of writing samples, which are rarely available in such quantities in historical contexts.
Dr. Vincent Christlein
Chair of Computer Science 5 (Pattern Recognition)
Phone +49 9131 8520281
https://lme.tf.fau.de/pattern-recognition-blog/spatio-temporal-handwriting-imita... - detailed information on the results is available on the website of the Pattern Recognition Lab
Dr. Susanne Langer | idw - Informationsdienst Wissenschaft
New method for simulating yarn-cloth patterns to be unveiled at ACM SIGGRAPH
09.07.2020 | Association for Computing Machinery
Virtual Reality Environments for the Home Office
09.07.2020 | Universität Stuttgart
New insight into the spin behavior in an exotic state of matter puts us closer to next-generation spintronic devices
Aside from the deep understanding of the natural world that quantum physics theory offers, scientists worldwide are working tirelessly to bring forth a...
Kiel physics team observed extremely fast electronic changes in real time in a special material class
In physics, they are currently the subject of intensive research; in electronics, they could enable completely new functions. So-called topological materials...
Solar cells based on perovskite compounds could soon make electricity generation from sunlight even more efficient and cheaper. The laboratory efficiency of these perovskite solar cells already exceeds that of the well-known silicon solar cells. An international team led by Stefan Weber from the Max Planck Institute for Polymer Research (MPI-P) in Mainz has found microscopic structures in perovskite crystals that can guide the charge transport in the solar cell. Clever alignment of these "electron highways" could make perovskite solar cells even more powerful.
Solar cells convert sunlight into electricity. During this process, the electrons of the material inside the cell absorb the energy of the light....
Empa researchers have succeeded in applying aerogels to microelectronics: Aerogels based on cellulose nanofibers can effectively shield electromagnetic radiation over a wide frequency range – and they are unrivalled in terms of weight.
Electric motors and electronic devices generate electromagnetic fields that sometimes have to be shielded in order not to affect neighboring electronic...
A promising operating mode for the plasma of a future power plant has been developed at the ASDEX Upgrade fusion device at Max Planck Institute for Plasma...
07.07.2020 | Event News
02.07.2020 | Event News
19.05.2020 | Event News
10.07.2020 | Life Sciences
10.07.2020 | Materials Sciences
10.07.2020 | Life Sciences