Orientation Field Estimation for Embedded Fingerprint Authentication System

Abstract

Orientation field (OF) estimation is a fundamental process in fingerprint authentication systems. In this paper, a novel binary pattern based low-cost OF estimation algorithm is proposed. The new method consists of two modules. The first is block-level orientation estimation and averaging in vector space by pixel level orientation statistics. The second is orientation quantization and smoothing. In the second module, the continuous orientation is quantized into fixed orientations with sufficient resolution (interval between fixed orientations). An effective smoothing scheme on the quantized orientation space is also proposed. The proposed algorithm is capable of stably processing poor-quality fingerprint images and is validated by tests conducted on an adaptive OF matching scheme. The proposed algorithm is also implemented into a fingerprint System on Chip (SoC) to comfirm that it satisfies the strict requirements of embedded system.