Color, which is effective information for computer vision, is vulnerable to variations in illumination. It is necessary to achieve illumination invariance for the description of an image’s color information. We propose two new color spaces that are robust to illumination changes: the color information color space based on the diagonal-offset model and the edge color space, the two channels of which are derived from the spherical color space and the linear transformation between the dark channel and the bright channel. Then, we propose a color moment invariant descriptor according to Hu moment invariants in the two new color spaces. We test the performance of the color descriptors with illumination variations in the context of object recognition and image retrieval. Experiments show that our descriptor has satisfactory stability for light variations. |
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RGB color model
Image retrieval
Curium
Object recognition
Mathematical modeling
Data modeling
Reflectivity