Illumination Normalization Using Local Graph Structure

The problem associated with Illumination variation is one of the major problems in image processing, pattern recognition, medical image, etc; hence there is a need to handle and deal with such variations. This paper presents a novel and efficient algorithm for images illumination correction call local graph structure (LGS). LGS features are derived from a general definition of texture in a local graph neighborhood. The idea of LGS comes from a dominating set for a graph of the image. The experiments results on ORL face database images demonstrated the effectiveness of the proposed method. The new LGS method can be stabilized more quickly and obtain higher correct rate compare to local binary pattern (LBP). Finally, LGS is simple and can be easily applied in many fields, such as image processing, pattern recognition, medical image as preprocessing