多母小波多消失矩最优小波包滤波器的研究

Optical Wavelet Packet Filter of Multi-mother Multi-vanishing Moments Joint Best Basis for Iris Recognition

采用层叠算法,计算小波包基函数的离散逼近序列。改进特征图像相关识别方法,选用识别能力评价指标,利用图像和小波包基函数相关的直接变换优点改进最优基选择,提出多母小波多消失矩最优基。生成最优基的特征图像,采用体全息相关识别系统实现虹膜的光学识别,实验取得较好的效果。设计、制作多母小波多消失矩最优基光学小波包灰阶滤波器以进一步提升识别率。检测表明,滤波器符合设计要求。实验表明,该滤波器可有效提高识别率。

Using the cascade algorithm, the discrete approximation sequences of wavelet packet basis functions are computed. With the advantage of direct transform through correlation between wavelet packet basis function and the input image,the eigen-image correlation based recognition method is modified. The criterion for basis selection is changed for iris recognition. The multi-mother multi-vanishing moments joint best basis selection algorithm is proposed. After joint best basis selection,eigen-images are generated and applied in a volume holographic correlation recognition system to implement optical iris recognition. A good identification rate is obtained. For better recognition performance, optical filter of the best basis is designed and fabricated. The experimental result shows the optical wavelet packet gray scale filter promotes the recognition capacity of the system.