Thesis (Ph. D.)--University of Wisconsin--Madison, 1968. / Typescript. Vita. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 1988. / Includes appendixes. Includes bibliographical references (leaves 86-87).

Thesis (M.S.)--Rochester Institute of Technology, 1993. / Typescript. Includes bibliographical references (leaves 138-139).

Thesis (Ph.D.(Electrical, Electronic and Computer Engineering))--University of Pretoria, 2008. / Includes bibliographical references (leaves 97-104)

Many items encoded into episodic memory are highly similar – seeing a stranger’s car may result in a memory representation which overlaps in many features with the memory of your friend’s car. To avoid falsely recognising the novel but similar car, it is important for the representations to be distinguished in memory. Even in healthy young adults failures of this mnemonic discrimination lead relatively often to false recognition, and such errors become substantially more frequent in older age. Whether an item’s representation is discriminated from similar memory representations depends critically on how it is encoded. However, the precise encoding mechanisms involved remain poorly understood. Establishing the determinants of successful mnemonic discrimination is essential for future research into strategies or interventions to prevent recognition errors, particularly in the context of age-related decline. A fuller understanding of age-related decline in mnemonic discrimination can also inform basic models of memory. This thesis evaluated the contribution of encoding processes to mnemonic discrimination both in young adults and in ageing, within the framework of two prominent accounts of recognition memory, the pattern separation account (Wilson et al., 2006) and Fuzzy Trace Theory (FTT; Brainerd & Reyna, 2002). Firstly, a functional magnetic resonance imaging study in young adults found evidence for differences in regions engaged at encoding of images according to the accuracy of later mnemonic discrimination, consistent with both pattern separation and FTT. Evidence of functional overlap between regions showing activity consistent with pattern separation, and activity associated with later accurate recognition was consistent with a role of cortical pattern separation in successful encoding, but there was no direct evidence that cortical pattern separation contributed to mnemonic discrimination. This first evidence of cortical pattern separation in humans was supported by findings that in the majority of pattern separation regions, response functions to stimuli varied in their similarity to previous items were consistent with predictions of computational models. Regional variation in the dimension(s) of similarity (conceptual/perceptual) driving pattern separation was indicative of variation in the type of mnemonic interference minimised by cortical pattern separation. Further evidence of encoding contributions to mnemonic discrimination was provided by an event-related potential study in young and older adults. Older adults showed less distinct waveforms than young adults at encoding of items whose similar lures were later correctly rejected compared to those falsely recognised, supporting the proposal that age-related encoding impairments contribute to the decline in mnemonic discrimination. Finally, a set of behavioural studies found that older adults’ mnemonic discrimination deficit is increased by conceptual similarity, supporting previous findings and consistent with FTT’s account of greater emphasis by older adults on gist processing. However, older adults required greater reduction in perceptual or conceptual similarity in order to successfully reject lures, as uniquely predicted by the pattern separation account. Together, the findings support the notion that encoding processes contribute directly to mnemonic discrimination and its age-related decline. An integrated view of the pattern separation account and FTT is discussed and developed in relation to the current findings.

As the demand for higher and more sophisticated security solutions has dramatically increased, a trustworthy and a more intelligent authentication technology has to takeover. That is biometric authentication. Although biometrics provides promising solutions, it is still a pattern recognition and artificial intelligence grand challenge. More importantly, biometric data in itself are vulnerable and requires comprehensive protection that ensures their security at every stage of the authentication procedure including the processing stage. Without this protection biometric authentication cannot replace traditional authentication methods. This protection however cannot be accomplished using conventional cryptographic methods due to the nature of biometric data, its usage and inherited dynamical changes. The new protection method has to transform the biometric data into a secure domain where original information cannot be reversed or retrieved. This secure domain has also to be suitable for accurate authentication performance. In addition, due to the permanence characteristic of the biometric data and the limited number of valid biometrics for each individual, the transform has to be able to generate multiple versions of the same original biometric trait. This to facilitate the replacement and the cancellation of any compromised transformed template with a newer one without compromising the security of the system. Hence the name of the transform that is best known as cancellable biometric. Two cancellable face biometric transforms have been designed, implemented and analysed in this thesis, the Polynomial and Co-occurrence Mapping (PCoM) and the Randomised Radon Signatures (RRS). The PCoM transform is based on high-order polynomial function mappings and co-occurrence matrices derived from the face images. The secure template is formed by the Hadamard product of the generated metrics. A mathematical framework of the two-dimensional Principal Component Analysis (2DPCA) recognition is established for accuracy performance evaluation and analysis. The RRS transform is based on the Radon Transform (RT) and the random projection. The Radon Signature is generated from the parametric Radon domain of the face and mixed with the random projection of the original face image. The transform relies on the extracted signatures and the Johnson-Lindenstrauss lemma for high accuracy performance. The Fisher Discriminant Analysis (FDA) is used for evaluating the accuracy performance of the transformed templates. Each of the transforms has its own security analysis besides a comprehensive security analysis for both. This comprehensive analysis is based on a conventional measure for the Exhaustive Search Attack (ESA) and a new derived measure based on the lower-bound guessing entropy for Smart Statistical Attack (SSA). This entropy measure is shown to be greater than the Shannon lower-bound of the guessing entropy for the transformed templates. This shows that the transforms provide greater security while the ESA analysis demonstrates immunity against brute force attacks. In terms of authentication performance, both transforms have either maintained or improved the accuracy of authentication. The PCoM has maintained the recognition rates for the CMU Advance Multimedia Processing Lab (AMP) and the CMU Pose, Illumination & Expression (PIE) databases at 98.35% and 90.13% respectively while improving the rate for the Olivetti Research Ltd (ORL) database to 97%. The transform has achieved a maximum recognition performance improvement of 4%. Meanwhile, the RRS transform has obtained an outstanding performance by achieving zero error rates for the ORL and PIE databases while improving the rate for the AMP by 37.50%. In addition, the transform has significantly enhanced the genuine and impostor distributions separations by 263.73%, 24.94% and 256.83% for the ORL, AMP and PIE databases while the overlap of these distributions have been completely eliminated for the ORL and PIE databases.

Thesis (M.S.)--Rochester Institute of Technology, 1989. / Includes bibliographical references (leaves 73-75).

Thesis (M.S.)--Rochester Institute of Technology, 1991. / Typescript. Includes bibliographical references.

We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face'' and "non-face'' prototype clusters. At each image location, the local pattern is matched against the distribution-based model, and a trained classifier determines, based on the local difference measurements, whether or not a human face exists at the current image location. We provide an analysis that helps identify the critical components of our system.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references (leaves 116-119). Also available on the Internet.