韦伯局部描述子(Weber Local Descriptor,WLD)被广泛用在多个领域,但由于其所具有的局限性使它对图像中的位移和旋转不具有较好的鲁棒性。因此,本文对WLD进行改进,首先,提出一种多尺度可变曲率Gabor滤波器对指静脉图像进行滤波,得到多...韦伯局部描述子(Weber Local Descriptor,WLD)被广泛用在多个领域,但由于其所具有的局限性使它对图像中的位移和旋转不具有较好的鲁棒性。因此,本文对WLD进行改进,首先,提出一种多尺度可变曲率Gabor滤波器对指静脉图像进行滤波,得到多尺度能量图和几何特征图;然后,用能量图计算差分激励,在计算时采用多尺度局部窗口,并加入方向信息;最后将几何特征图和差分激励结合形成特征。该方法的有效性将在FV-TJ和FV-USM数据库上进行验证,结果表明本文方法的识别性能要优于其他方法。展开更多
Biometrics is becoming an important method for human identification. However, once a biometric pattern is stolen, the user will quickly run out of alternatives and all the applications where the associated biometric p...Biometrics is becoming an important method for human identification. However, once a biometric pattern is stolen, the user will quickly run out of alternatives and all the applications where the associated biometric pattern is used become insecure. Cancelable biometrics is a solution. However, traditional cancelable biometric methods treat the transformation process and feature extraction process independently. As a result, this kind of cancelable biometric approach would reduce the recognition accuracy. In this paper, we first analyzed the limitations of traditional cancelable biometric methods, and proposed the Key Incorporation Scheme for Cancelable Biometrics approach that could increase the recognition accuracy while achieving “cancelability”. Then we designed the Gabor Descriptor based Cancelable Iris Recognition method that is a practical implementation of the proposed Key Incorporation Scheme. The experimental results demonstrate that our proposed method can significantly improve the iris recognition accuracy while achieving “cancelability”.展开更多
文摘韦伯局部描述子(Weber Local Descriptor,WLD)被广泛用在多个领域,但由于其所具有的局限性使它对图像中的位移和旋转不具有较好的鲁棒性。因此,本文对WLD进行改进,首先,提出一种多尺度可变曲率Gabor滤波器对指静脉图像进行滤波,得到多尺度能量图和几何特征图;然后,用能量图计算差分激励,在计算时采用多尺度局部窗口,并加入方向信息;最后将几何特征图和差分激励结合形成特征。该方法的有效性将在FV-TJ和FV-USM数据库上进行验证,结果表明本文方法的识别性能要优于其他方法。
文摘Biometrics is becoming an important method for human identification. However, once a biometric pattern is stolen, the user will quickly run out of alternatives and all the applications where the associated biometric pattern is used become insecure. Cancelable biometrics is a solution. However, traditional cancelable biometric methods treat the transformation process and feature extraction process independently. As a result, this kind of cancelable biometric approach would reduce the recognition accuracy. In this paper, we first analyzed the limitations of traditional cancelable biometric methods, and proposed the Key Incorporation Scheme for Cancelable Biometrics approach that could increase the recognition accuracy while achieving “cancelability”. Then we designed the Gabor Descriptor based Cancelable Iris Recognition method that is a practical implementation of the proposed Key Incorporation Scheme. The experimental results demonstrate that our proposed method can significantly improve the iris recognition accuracy while achieving “cancelability”.
