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Most, if not all, assessments or comparisons of biometric systems focus on extrinsic characteristics; our focus is intrinsic, as we are concerned with the biometric signals and images that underpin each system, and not with how these signals are obtained, matched or interpreted. Through the intrinsic assessment of a biometric system, we expect to answer several policy-related questions, including: How robust is the system? How can the system be refined? To what extent is the system intrinsically prone to error? Likewise, through the intrinsic comparison of two or more biometric systems, we expect to answer questions concerning: To what extent is the system complementary? Can a more robust, hybrid system be identified? As with any assessment or comparative analysis of a number of systems, it is necessary to carry out the analysis within a consistent framework or model. After considering a number of approaches, we employ the wavelet transform technique because of its robustness in modeling most, if not all, of the biometric signals and images and its ability to shed light on the above policy-related questions.