On-line counting of pests in a greenhouse using computer vision

International audienceThis article is concerned with the on-line counting of some harmful insects in videos in the framework of in situ video-surveillance that aims at the early detection of pest attacks in greenhouse crops. The challenges mainly concern the tiny resolution and color contrast of the insects of interest in the videos, the outdoor issues and the quasi-real time constraints. Thus, we propose a complete video-processing chain that can cope with such challenges quite satisfactorily while yielding an acceptable performance. The system has been validated off-line against many recorded videos for the whiteflie species (one potential harmful pest species)

On-line video recognition and counting of harmful insects

International audienceThis article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues and the video-processing which needs to be done in quasi-real time. Thus, we propose an approach which makes use of a pattern recognition algorithm to extract the locations of the harmful insects of interest in a video, which we combine with some videoprocessing algorithms in order to achieve an on-line video-surveillance solution. The system has been validated off-line on the whiteflie species (one potential harmful insect) and has shown acceptable performance in terms of accuracy versus computational time

Analyse spatio-temporelle de séquences d'images issues de la video-microscopie de fluorescence 3D+T

Diplôme : Dr. d'Universit

A model selection approach for robust spatio-temporal analysis of dynamics in 4D fluorescence videomicroscopy

International audienceWe describe a novel automatic approach for vesicle trafficking analysis in 3D+T videomicroscopy. Tracking individually objects in time in 3D+T videomicroscopy is known to be a very tedious job and leads generally to unreliable results. So instead, our method proceeds by first identifying trafficking regions in the 3D volume and next analysing at them the vesicle trafficking. The latter is viewed as significant change in the fluorescence of a region in the image. We embed the problem in a model selection framework and we resolve it using dynamic programming. We applied the proposed approach to analyse the vesicle dynamics related to the trafficking of the RAB6A protein between the Golgi apparatus and ER cell compartments

Reliable motion detection and analysis in live-cell imaging

International audienc