The Color Image team designs automatic analysis schemes for images that represent the color information in observed scenes. Its researchers work on
- Extracting local or global features from CFA or raw images acquired by color cameras equipped with one sensor,
- Selecting color spaces that are adapted to the segmentation of full color images that have been provided by three-sensor cameras,
- Recognizing objects under uncontrolled acquisition conditions by the analysis of multi-spectral images in the visible spectrum.

• color vision system which detects aspect flaws occurring on the color surfaces of drinking glasses decorated thanks to an industrial silk-screen process

• embedded vision system which measures the cross section of catenary contact wire

• color vision system that inspects the frozen meat.

We also develop automatic diagnostic of turbo-alternator by pattern recognition with L2EP Institute.