Date: Fri. June 19, 2026
Event: FAU MoD Lecture
Organized by: FAU MoD, the Research Center for Mathematics of Data at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
FAU MoD Lecture: Reverse typography and the theory of shape: Can old books be brought back to life?
Speaker: Prof. Dr. Jean‑Michel Morel
Affiliation: Division of Industrial Data Science. School of Data Science, Lingnan University (Hong Kong)
Abstract. Reverse typography is a technique that enables the shapes of printed characters to be extracted from scanned documents in digital form, recognised, and restored in a printable format. One of the aims of the technique developed by my team is to contribute to the history of typography. A more ambitious goal is to breathe new life into the many high-interest books gathering dust on library shelves, making them accessible in a fully digitised form that retains the original appearance. This will lead me to discuss how to overcome one of the main pitfalls of artificial intelligence: its tendency to ‘hallucinate’. I will illustrate my talk with experiments performed on images of scanned books, shapes, and Chinese characters. In doing so, I will touch upon the underlying techniques stemming from the mathematical theory of planar shapes, the PDEs handling them, and their use in computer graphics.
OUR SPEAKER
Jean-Michel Morel started his career as teaching assistant in mathematics at University of Marseille, and obtained his doctorate at Sorbonne University in 1985. He then held professor positions in applied mathematics at Paris Sciences & Lettres University, Paris-Saclay University, City University of Hong Kong, and is currently chair professor in data science at Lingnan University. Trained as a pure mathematician and a specialist of partial differential equations, Jean-Michel Morel took an early interest in computer vision and AI and specialized in the mathematical formalization of visual perception. This led him to conceive theories for the use of PDEs and variational methods in image processing, and to the design of image analysis algorithms. His algorithms have been implemented in imaging systems such as earth observation satellites, medical devices, industrial cameras and mobile phones.
AUDIENCE
This is a hybrid event (On-site/online) open to: Public, Students, Postdocs, Professors, Faculty, Alumni and the scientific community all around the world.
WHEN
Fri. June 19, 2026 at 11:15H (Berlin time)
WHERE
On-site / Online
[On-site] Friedrich-Alexander-Universität Erlangen-Nürnberg.Room H21
Cauerstraße 5b, 91058 Erlangen [Online] https://www.fau.tv/clip/id/63064
Shortlink to share this event: https://go.fau.de/1e-dd
You might like:
• FAU MoD Lectures
• Upcoming events
• FAU MoD Courses & Workshops
• MLPDES26, Machine Learning and PDEs Workshop (2026)
• FAU MoD Lecture: Breaking Nonconvexity: Consensus-Based Optimization by Prof. Dr. Massimo Fornasier
• FAU MoD Lecture: A data-driven approach to closed-loop control of wound state progression to drive healing outcomes by Prof. Dr. Marcella M. Gomez
• FAU MoD Lecture: Data Driven Modeling for Scientific Discovery and Digital Twins by Prof. Dr. Dongbin Xiu
• FAU MoD Lecture: A long life: How desirable is it, evolutionarily speaking? by Prof. Dr. Hanna Kokko
• FAU MoD Lecture: Bridging numerics and scientific machine learning for industrial applications by Dr. Christopher Straub
• FAU MoD Workshop: FAU MoD Workshop (Dec. 2025) by Prof. Giovanni Fantuzzi | Prof. Denisa Martonova
• FAU MoD Lecture: Quantum firmware: optimal control for quantum processors by Prof. Dr. Tommaso Calarco
• FAU MoD Lecture: AI Components in PDE Solvers by Prof. Dr. Nils Thürey
• FAU MoD Lecture: Disruption in science and engineering happens at scale by Prof. Dr. Johannes Brandstetter
• FAU MoD Workshop: FAU MoD Workshop (Sep. 2025) by Prof. Lorenzo Liverani | Prof. Hagen Holthusen
• FAU MoD Lecture: Exemplary applications of machine learning and optimization in quantum chemistry by Prof. Dr. Andreas Görling
• FAU MoD Lecture & workshop: AI for maths and maths for AI by Dr. François Charton
• FAU MoD Lecture: Optimization-based control for large-scale and complex systems: When and why does it work? by Prof. Dr. Lars Grüne
• FAU MoD Lecture: Mathematics of neural stem cells: Linking data and processes by Prof. Dr. Ana Martin-Villalba
• FAU MoD Lecture: FAU MoD Lecture S. Jin / N. Liu (double session) by Prof. Dr. Shi Jin and Prof. Dr. Nana Liu
• FAU MoD Lecture: Do you think you understand sex and death? Why predictions about biological processes require more than just intuition by Prof. Dr. Hanna Kokko
• FAU MoD Lecture: FAU MoD Lecture. Special December 2024 by Prof. Dr. Holger Rauhut and Prof. Dr. Christian Bär
• FAU MoD Lecture: Measuring productivity and fixedness in lexico-syntactic constructions by Prof. Dr. Stephanie Evert
• FAU MoD Lecture: New avenues for the interaction of computational mechanics and machine learning by Prof. Dr. Paolo Zunino
• FAU MoD Lecture: Discovering and Communicating Excellence by Prof. Dr. Ute Klammer
• FAU MoD Lecture: Thoughts on Machine Learning by Prof. Dr. Rupert Klein
• FAU MoD Lecture: Using system knowledge for improved sample efficiency in data-driven modeling and control of complex technical systems by Prof. Dr. Sebastian Peitz
• FAU MoD Lecture: Image Reconstruction – The Dialectic of Modelling and Learning by Prof. Dr. Martin Burger
• FAU MoD Lecture: The role of Artificial Intelligence in the future of mathematics by Prof. Dr. Amaury Hayat
• FAU MoD Lecture: FAU MoD Lecture. Special November 2023 by Prof. Dr. Michael Kohlhase and Prof. Dr. Edriss S. Titi
• FAU MoD Lecture: Free boundary regularity for the obstacle problem by Prof. Dr. Alessio Figalli
• FAU MoD Lecture: Physics-Based and Data-Driven-Based Algorithms for the Simulation of the Heart Function by Prof. Dr. Alfio Quarteroni
• FAU MoD Lecture: From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus? by Prof. Dr. George Karniadakis
• FAU MoD Lecture: From Alan Turing to contact geometry: Towards a “Fluid computer” by Prof. Dr. Eva Miranda
• FAU MoD Lecture: Applications of AAA Rational Approximation by Prof. Dr. Nick Trefethen
• FAU MoD Lecture: Learning-Based Optimization and PDE Control in User-Assignable Finite Time by Prof. Dr. Miroslav Krstic
_
Don’t miss out our last news and connect with us!
