The Color Imaging 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 multispectral images in the visible and near infrared spectrum.
Our main application field is the quality or dimension control of manufactured objects, for example:
- 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 have also worked on the automatic diagnostic of turbo-alternators by pattern recognition with L2EP Laboratory.