Biblio

Iris recognition is one of the most reliable biometrics for identification purpose in terms of reliability and accuracy. Hence, in this research the integration of cancelable biometrics features for iris recognition using encryption and decryption non-invertible transformation is proposed. Here, the biometric data is protected via the proposed cancelable biometrics method. The experimental results showed that the recognition rate achieved is 99.9% using Bath-A dataset with a maximum decision criterion of 0.97 along with acceptable processing time.

Using shape context descriptors in the distance uneven grouping and its more extensive description of the shape feature, so this descriptor has the target contour point set deformation invariance. However, the twisted adhesions verification code have more outliers and more serious noise, the above-mentioned invariance of the shape context will become very bad, in order to solve the above descriptors' limitations, this article raise a new algorithm based on the relative shape context and point pattern matching to identify codes. And also experimented on the CSDN site's verification code, the result is that the recognition rate is higher than the traditional shape context and the response time is shorter.