Thresholded two-phase test sample representation for outlier rejection in biological recognition

The two-phase test sample representation (TPTSR) was proposed as a useful classifier for face recognition. However, the TPTSR method is not able to reject the impostor, so it should be modified for real-world applications. This paper introduces a thresholded TPTSR (T-TPTSR) method for complex object recognition with outliers, and two criteria for assessing the performance of outlier rejection and member classification are defined. The performance of the T-TPTSR method is compared with the modified global representation, PCA and LDA methods, respectively. The results show that the T-TPTSR method achieves the best performance among them according to the two criteria.