Iris Location Algorithm And Its Embedded Software Platform Design

Iris recognition is an emerging biometrics technology. Compared with the other biometrics technologies (fingerprint recognition, facial recognition voice recognition, etc.), iris recognition has the following characteristics: stability, high reliability, non-contact. Therefore, it will be widely used in the future.This thesis made research and improvement of the iris recognition kernel algorithms. The main tasks of this thesis include:First, at the iris image localization stage, two new localization methods are proposed. The first method is based on gray information and fractional differential. In iris inner localization, compare with iris outer localization, iris inner localization is simple, so use the fast method based gray information. In iris outer localization, use fractional differential edge detection. The second method is based on SUSAN edge detector. This method is emphasized on iris outer localization. The SUSAN edge detector has the integral characteristic, so it will not depauperate much iris texture. Also, SUSAN edge detector will not impacted by local noise.Second, at the normalization stage, we propose a polar coordinate transform resolution. Use concentric circle as the normalization style. Take illumination estimation to change the low contrast of mormalized image. Also, to enhance image, we use bicubic interpolation and histogram equalization.Third, introduce the hardware of embedded iris recognition system, design DSP/BIOS based on TI DSP. Transplant and optimize the algorithm to TI TMS320 C6713b DSPs platform.The algorithm experiments are done in the CASIA iris database (version 2.0) and Lab iris database, and good recognition results are achieved.