Production of scientific images is ubiquitous in many scientific disciplines as they can capture phenomena in a broad range of lengthscales, from the stars to the atom.
Therefore, skills in image processing can be advantageous to perform and automate image analysis in many applications. This lecture will have a tutorial/workshop format and will mainly focus on the library scikit-image [1,2]. This course will be taught in English in case of non-French speaking attendees. The lecturer is one of the scikig-image developers.
Prerequisites: Even if a basic knowledge of Python and numpy is recommended (cf Sessions 1 & 2 of "Cours de «Python pour la physique»"), a reminder will the provided at the beginning of the session to ensure that attendees can step up easily. A laptop with Python installed is highly recommended.
- Reminder (Containers in Python, numpy, scipy, matplotlib)
- Jupyter, a notebook
- Brief introduction to virtual environments
- Presentation of image-related libraries available in Python
- More detailed presentation of scikit-image (documentation, source-code, etc.)
- Read and write (IO) images and their representations
- Histogram and thresholding
- Filters and peak finding
- Feature detection and characterization
- Image transformation and displacement detection
- Image restoration
- Image stitching
Dates and location:
Tuesday 28th March and Tuesday 4th April 2017, 9-12am and 2-5pm
salle 161, 1er étage au Laboratoire de Physique des Solides, Bâtiment 510, Orsay
Announcement and registration (you must write to Laura Ledez):