Fingerprint and Iris Recognition Using Cross Correlation

Abstract: Fingerprint – Iris recognition is done using many ways, we propose to use bifurcations along with ridge patterns to identify the fingerprint image and canny edge features to identify iris image. The ridges along with bifurcations are considered as minutiae of fingerprint. These minutiae along with their position (ie; x and y co- ordinates) and orientations are saved as features. We propose an novel matching scheme to detect the matched minutiae of pairs incrementally. The iris features are effective captured using edge detection algorithm. Following that, the maximum score is computed through cross correlation and used as the recognition parameters. This way of combination has provided efficient recognition results which had overcome the existing drawbacks. The experiments were conducted using FVC 2004 dataset images.

Keywords: Multimodal biometrics, fingerprint recognition, minutiae, iris recognition, Cross Correlation