Multimodal of Face and Iris Based on Local Binary Pattern and Gabor-Zernike Moments

Abstract

This paper presents the multimodal of face and iris based on the same feature extraction techniques for the both traits. For locating the iris, compute the next three neighbour-pixels from the pupil-circle in horizontal-right and horizontal-left, and if it found the value of those pixels are close to the sclera values (because it is close to the white color), then it will stop otherwise continue to the next pixels. The radius of the iris is obtained from the number of skipped-pixels. The iris is normalized by using the Rubber Sheet Normalization. The texture features of iris and face were extracted by using the Local Binary Pattern (LBP) and Gabor-Zernike Moments. Different classifications were used to evaluate the proposed system. The experiment was performed on the ORL and CASIA-Iris databases and the performance of the system is found to be satisfactory.

Composite Feature Extraction and Classification for Fusion of Palm-Print and Iris Biometric Traits

“…The palm is segmented from the rest parts of the hand by using an algorithm from our previous work [11]. Iris was localized by using the NPVA [12]. Texture features of iris and palm were extracted by computing the mean and standard deviation of the local binary pattern (LBP).…”