We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach.
- Authors
Dimiccoli, Mariella; Jacob, Jean-Pascal; Moisan, Lionel
- Abstract
This paper proposes a probabilistic approach for the detection and the tracking of particles in fluorescent time-lapse imaging. In the presence of a very noised and poor-quality data, particles and trajectories can be characterized by an a contrario model, that estimates the probability of observing the structures of interest in random data. This approach, first introduced in the modeling of human visual perception and then successfully applied in many image processing tasks, leads to algorithms that neither require a previous learning stage, nor a tedious parameter tuning and are very robust to noise. Comparative evaluations against a well-established baseline show that the proposed approach outperforms the state of the art.
- Subjects
IMAGE recognition (Computer vision); FLOW visualization; COMPUTER simulation; IMAGE denoising; VISUAL perception; COMPUTER algorithms
- Publication
Machine Vision & Applications, 2016, Vol 27, Issue 4, p511
- ISSN
0932-8092
- Publication type
Article
- DOI
10.1007/s00138-016-0757-7