Bimodal palm biometric feature extraction using a single RGB image
Teodors Eglītis, Mihails Pudžs, Modris Greitāns · International Conference on Biometrics · 2014
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 non-linear 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.