This paper investigates new approaches for improving the conventional palmprint authentication performance by integrating color information. We firstly propose a new approach for image level combination of multiple color components to generate more reliable palmprint representation than the conventional gray level representation. This investigation is motivated to develop more robust palmprint representation that can be employed to achieve better performance for the conventional palmprint identification, with the same computational complexity. Secondly, this paper presents a rigorous analysis of different color representations for the palmprint images to ascertain the performance improvement using different feature representations (OLOF and SIFT) and different databases (scanner and webcam). The rigorous experimental results from this study suggest that the influence of color information can differently alter the performance gain, which varies with the nature of employed feature representation.