Michaël Roynard

LRE, EPITA

14-16 rue Voltaire

94270 Le Kremlin-Bicêtre, France

Hello, and welcome to my personal webpage. I am Michaël, a postdoctoral researcher at the LRE in France. My research is in theoretical computer science applied to image processing. During my Ph.D. I designed a complete Concept framework for the image-processing domain, delivered through the modern C++ Pylene library.

I now investigate how to bridge the static world (C++ generic code) and the dynamic world (Python), where most of the image-processing community resides — exploring avenues such as JIT compilation to produce optimal Python bindings on-the-fly, on demand from the practitioner.

On a personal note, I am active on Reddit (r/cpp). I like to read good books, travel and see interesting places, good (French) food, and good music such as Pink Floyd, Rammstein, and the like.

news

Jun 01, 2026	Personal website rebuilt on a modern al-folio and back online. 🎉

selected publications

RRPR
An Image Processing Library in Modern C++: Getting Simplicity and Efficiency with Generic Programming

Michaël Roynard, Edwin Carlinet, and Thierry Géraud

In Reproducible Research in Pattern Recognition, 2019

Abs Bib

As there are as many clients as many usages of an Image Processing library, each one may expect different services from it. Some clients may look for efficient and production-quality algorithms, some may look for a large tool set, while others may look for extensibility and genericity to inter-operate with their own code base...but in most cases, they want a simple-to-use and stable product. For a C++ Image Processing library designer, it is difficult to conciliate genericity, efficiency and simplicity at the same time. Modern C++ (post 2011) brings new features for library developers that will help designing a software solution combining those three points. In this paper, we develop a method using these facilities to abstract the library components and augment the genericity of the algorithms. Furthermore, this method is not specific to image processing; it can be applied to any C++ scientific library.
@inproceedings{roynard.2019.rrpr, address = {Cham}, author = {Roynard, Micha{\"e}l and Carlinet, Edwin and G{\'e}raud, Thierry}, booktitle = {Reproducible Research in Pattern Recognition}, editor = {Kerautret, Bertrand and Colom, Miguel and Lopresti, Daniel and Monasse, Pascal and Talbot, Hugues}, isbn = {978-3-030-23987-9}, pages = {121--137}, publisher = {Springer International Publishing}, title = {An Image Processing Library in Modern {C}++: Getting Simplicity and Efficiency with Generic Programming}, year = {2019} }
GPCE
A Modern C++ Point of \emphView of Programming in Image Processing

Michaël Roynard, Edwin Carlinet, and Thierry Géraud

In Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences (GPCE ’22), December 06–07, 2022, Auckland, New Zealand, Dec 2022

Abs DOI Bib

C++ is a multi-paradigm language that enables the programmer to set up efficient image processing algorithms easily. This language strength comes from many aspects. C++ is high-level, so this enables developing powerful abstractions and mixing different programming styles to ease the development. At the same time, C++ is low-level and can fully take advantage of the hardware to deliver the best performance. It is also very portable and highly compatible which allows algorithms to be called from high-level, fast-prototyping languages such as Python or Matlab. One fundamental aspects where C++ shines is generic programming. Generic programming makes it possible to develop and reuse bricks of software on objects (images) of different natures (types) without performance loss. Nevertheless, conciliating genericity, efficiency, and simplicity at the same time is not trivial. Modern C++ (post-2011) has brought new features that made it simpler and more powerful. In this paper, we focus on some C++20 aspects of generic programming: ranges, views, and concepts, and see how they extend to images to ease the development of generic image algorithms while lowering the computation time.
@inproceedings{roynard.2022.gpce, address = {Auckland, New Zealand}, author = {Roynard, Micha\"el and Carlinet, Edwin and G\'eraud, Thierry}, booktitle = {Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences (GPCE '22), December 06--07, 2022, Auckland, New Zealand}, doi = {10.1145/3564719.3568692}, isbn = {978-1-4503-9920-3}, lrdekeywords = {Image,genericity,views}, lrdenewsdate = {2022-10-10}, lrdeprojects = {Olena}, lrdestatus = {accepted}, month = dec, title = {A Modern {C}++ Point of \emph{View} of Programming in Image Processing}, year = {2022} }