Local Color Descriptor for Object Recognition across Illumination Changes

In the context of object recognition, it is useful to extract, from the images, efficient local descriptors that are insensitive to the illumination conditions, to the camera scale factor and to the position and orientation of the object. In this paper, we propose to cope with this invariance problem by applying a spatial transformation to the local regions around detected key points. The new position of each pixel after this local spatial transformation is evaluated according to both the colors and the relative positions of all the pixels in the original local region. The descriptor of the considered local region is the set of the new positions of three particular pixels in this region. The invariance and the discriminating power of our local descriptor is assessed on a public database.