Bimodal palm biometric feature extraction using a single RGB image

Abstract

This paper proposes a method for palm bimodal biometric feature (vein and crease pattern) acquisition from a single RGB image. Typical bimodal biometric systems require combining infrared and visible images for this task. We use a single CMOS color sensor and a specific illumination comprising of two wavelengths to acquire the image. As a result each biometric modality is more pronounced in its own color channel. The image is processed by applying adapted matched filters with nonlinear modifications. Performance of the proposed method is evaluated against feature separation with optical band-pass and band-stop approach on a database of 64 people. The results show the average true positive rate is 70.6 \% for vein detection and 64.7 \% for crease detection, whereas in 14.8 \% and 9.29 \% of the cases feature of wrong modality is detected.