In this chapter, we design a novel red-green-blue and depth-based four-camera system that can capture palm-related images separately in real time. Techniques of region of interest location, ROI alignment, and light source intensity optimization are studied. The ROI location method is modified to increase the robustness of hand gesture variation. Based on depth information, we propose the coordinate mapping and inclination rectification methods to obtain aligned ROI pairs. Using this device, we collect a video-based multimodal palm image database. After parameter optimization and information fusion, the equal error rate of our approach on this database is lower than \( 0.47\% \) . The recognition rate obtained from support vector machine-based fusion is higher than \( 99.8\% \) . Experimental results prove that the proposed system achieves advantages of anti-spoofing, high speed, high accuracy, and small size.