Nowadays, video surveillance systems are very used to safeguard airport areas, train stations, public places, among others. Using these systems, the person re-identification is an automated task. However, there are many problems that affect the good performance of person re-identification algorithms. For example, illumination changes in the scenes is one of the essential problems. It increases the false colors on the person appearance. Moreover, in the extraction of low level features (color) there is a need to obtain reliable colors of the image or person appearance. To this end, we propose a new algorithm using full-quaternions for color image representation. The quaternionic trigonometry and the Quaternion Fast Fourier Transform are used to improve person image in the frequency domain. Finally, to see the transformed image, an adaptive gamma function is developed. Experiment results on two datasets (VIPeR and GRID) show consistent improvements over the state-of-the-art approaches.
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