Galaxy Filament Detection Using the Quality Candy Model

We propose to apply a marked point process to detect a galaxy filament network. From the "quality candy" model, initially developed for road network extraction in remotely sensed images, we adapt the data term to the filament detection. The optimization is realized by a simulated annealing using a reversible jump Markov Chain Monte Carlo algorithm. Results are presented on a numerical simulation and on an astronomical survey