Thesis (PhD (Electrical and Electronic engineering))--University of Stellenbosch, 2005. / Individuals can be identified by their handwriting. Signatures are, for example, currently used as a biometric identifier on documents such as cheques. Handwriting recognition is also applied to the recognition of characters and words on documents—it is, for example, useful to read words on envelopes automatically, in order to improve the efficiency of postal services. Handwriting is a dynamic process: the pen position, pressure and velocity (amongst others) are functions of time. However, when handwritten documents are scanned, no dynamic information is retained. Thus, there is more information inherent in systems that are based on dynamic handwriting, making them, in general, more accurate than their static counterparts. Due to the shortcomings of static handwriting systems, static signature verification systems, for example, are not completely automated yet. During this research, a technique was developed to extract dynamic information from static images. Experimental results were specifically generated with signatures. A few dynamic representatives of each individual’s signature were recorded using a single digitising tablet at the time of registration. A document containing a different signature of the same individual was then scanned and unravelled by the developed system. Thus, in order to estimate the pen trajectory of a static signature, the static signature must be compared to pre-recorded dynamic signatures of the same individual. Hidden Markov models enable the comparison of static and dynamic signatures so that the underlying dynamic information hidden in the static signatures can be revealed. Since the hidden Markov models are able to model pen pressure, a wide scope of signatures can be handled. This research fully exploits the modelling capabilities of hidden Markovmodels. The result is a robustness to typical variations inherent in a specific individual’s handwriting. Hence, despite these variations, our system performs well. Various characteristics of our developed system were investigated during this research. An evaluation protocol was also developed to determine the efficacy of our system. Results are promising, especially if our system is considered for static signature verification.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. / This thesis relates to the problem of deterministically tracking an object that moves in a video sequence. A variety image processing and contour fitting algorithms and techniques are discussed. The tracking algorithm fit B-spline templates as is set out in the work done by Blake and Isard. The method builds on the concept that only certain deformations of the moving object's bounding curve is allowed. This is governed by projection into a subspace that allow only the wanted deformations. The deformations are restricted to be mostly linear, but small, nonlinear deformations can also be accomodated.

<p>Much work has been done in building systems that can recognize gestures, e.g. as a component of sign language recognition systems. These systems typically use whole gestures as the smallest unit for recognition. Although high recognition rates have been reported, these systems do not scale well and are computationally intensive. The reason why these systems generally scale poorly is that they recognize gestures by building individual models for each separate gesture / as the number of gestures grows, so does the required number of models. Beyond a certain threshold number of gestures to be recognized, this approach become infeasible. This work proposed that similarly good recognition rates can be achieved by building models for subcomponents of whole gestures, so-called cheremes. Instead of building models for entire gestures, we build models for cheremes and recognize gestures as sequences of such cheremes. The assumption is that many gestures share cheremes and that the number of cheremes necessary to describe gestures is much smaller than the number of gestures. This small number of cheremes then makes it possible to recognized a large number of gestures with a small number of chereme models. This approach is akin to phoneme-based speech recognition systems where utterances are recognized as phonemes which in turn are combined into words.</p>

Biometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of civilian and government applications. The candidate modalities used in biometrics include retinas, fingerprints, signatures, audio, faces, etc. There are two types of biometric system: single modal systems and multiple modal systems. Single modal systems perform person recognition based on a single biometric modality and are affected by problems like noisy sensor data, intra-class variations, distinctiveness and non-universality. Applying multiple modal systems that consolidate evidence from multiple biometric modalities can alleviate those problems of single modal ones. Integration of evidence obtained from multiple cues, also known as fusion, is a critical part in multiple modal systems, and it may be consolidated at several levels like feature fusion level, matching score fusion level and decision fusion level. Among biometric modalities, both audio and face modalities are easy to use and generally acceptable by users. Furthermore, the increasing availability and the low cost of audio and visual instruments make it feasible to apply such Audio-Visual (AV) systems for security applications. Therefore, this dissertation proposes an algorithm of face recognition. In addition, it has developed some novel algorithms of fusion in different levels for multiple modal biometrics, which have been tested by a virtual database and proved to be more reliable and robust than systems that rely on a single modality. / by Lin Huang. / Thesis (Ph.D.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Most of the human visual field falls in the periphery, and peripheral processing is important for normal visual functioning. Yet, little is known about peripheral object recognition in naturalistic scenes and factors that modulate this ability. We propose that a critical function of scene and object memory is in order to facilitate visual object recognition in the periphery. In the first experiment, participants identified objects in scenes across different levels of familiarity and contextual information within the scene. We found that familiarity with a scene resulted in a significant increase in the distance that objects were recognized. Furthermore, we found that a semantically consistent scene improved the distance that object recognition is possible, supporting the notion that contextual facilitation is possible in the periphery. In the second experiment, the preview duration of a scene was varied in order to examine how a scene representation is built and how memory of that scene and the objects within it contributes to object recognition in the periphery. We found that the closer participants fixated to the object in the preview, the farther on average they recognized that target object in the periphery. However, only a preview duration of the scenes for 5000 ms produced significantly farther peripheral object recognition compared to not previewing the scene. Overall, these experiments introduce a novel research paradigm for object recognition in naturalistic scenes, and demonstrates multiple factors that have systematic effects on peripheral object recognition. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

In this study, we investigated what informational aspects of faces could account for the ability to match an individual’s face to their voice, using only static images. In each of the first six experiments, we simultaneously presented one voice recording along with two manipulated images of faces (e.g. top half of the face, bottom half of the face, etc.), a target face and distractor face. The participant’s task was to choose which of the images they thought belonged to the same individual as the voice recording. The voices remained un-manipulated. In Experiment 7 we used eye tracking in order to determine which informational aspects of the model’s faces people are fixating while performing the matching task, as compared to where they fixate when there are no immediate task demands. We presented a voice recording followed by two static images, a target and distractor face. The participant’s task was to choose which of the images they thought belonged to the same individual as the voice recording, while we tracked their total fixation duration. In the no-task, passive viewing condition, we presented a male’s voice recording followed sequentially by two static images of female models, or vice versa, counterbalanced across participants. Participant’s results revealed significantly better than chance performance in the matching task when the images presented were the bottom half of the face, the top half of the face, the images inverted upside down, when presented with a low pass filtered image of the face, and when the inner face was completely blurred out. In Experiment 7 we found that when completing the matching task, the time spent looking at the outer area of the face increased, as compared to when the images and voice recordings were passively viewed. When the images were passively viewed, the time spend looking at the inner area of the face increased. We concluded that the inner facial features (i.e. eyes, nose, and mouth) are not necessary informational aspects of the face which allow for the matching ability. The ability likely relies on global features such as the face shape and size. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

How does spatial organization of objects affect the perceptual processing of a scene? Surprisingly, little research has explored this topic. A few studies have reported that, when simple, homogenous stimuli (e.g., dots), are presented in a regular formation, they are judged to be more numerous than when presented in a random configuration (Ginsburg, 1976; 1978). However, these results may not apply to real-world objects. In the current study, fewer objects were believed to be on organized desks than their disorganized equivalents. Objects that are organized may be more likely to become integrated, due to classic Gestalt principles. Consequently, visual search may be more difficult. Such object integration may diminish saliency, making objects less apparent and more difficult to find. This could explain why, in the present study, objects on disorganized desks were found faster. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection

This dissertation introduces our work on face recognition using a novel approach based on creating 3D face model from 2D face images. Together with the pose angle estimation and illumination compensation, this method can be used successfully to recognize 2D faces with 3D recognition algorithms. The results reported here were obtained partially with our own face image database, which had 2D and 3D face images of 50 subjects, with 9 different pose angles. It is shown that by applying even the simple PCA algorithm, this new approach can yield successful recognition rates using 2D probing images and 3D gallery images. The insight gained from the 2D/3D face recognition study was also extended to the case of involving 2D probing and 2D gallery images, which offers a more flexible approach since it is much easier and practical to acquire 2D photos for recognition. To test the effectiveness of the proposed approach, the public AT&T face database, which had 2D only face photos of 40 subjects, with 10 different images each, was utilized in the experimental study. The results from this investigation show that with our approach, the 3D recognition algorithm can be successfully applied to 2D only images. The performance of the proposed approach was further compared with some of the existing face recognition techniques. Studies on imperfect conditions such as domain and pose/illumination variations were also carried out. Additionally, the performance of the algorithms on noisy photos was evaluated. Pros and cons of the proposed face recognition technique along with suggestions for future studies are also given in the dissertation. / by Guan Xin. / Thesis (Ph.D.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.

Contemporary computer vision solutions to the problem of object detection aim at incorporating contextual information into the process. This thesis proposes a systematic evaluation of the usefulness of incorporating knowledge about the geometric context of a scene into a baseline object detection algorithm based on local features. This research extends publicly available MATLABRª implementations of leading algorithms in the field and integrates them in a coherent and extensible way. Experiments are presented to compare the performance and accuracy between baseline and context-based detectors, using images from the recently published SUN09 dataset. Experimental results demonstrate that adding contextual information about the geometry of the scene improves the detector performance over the baseline case in 50% of the tested cases. / by Rafael J. Giusti Urbina. / Thesis (M.S.C.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

Underwater vehicles often use acoustics or dead reckoning for global positioning, which is impractical for low cost, high proximity applications. An optical based positional feedback system for a wave tank operated biomimetic station-keeping vehicle was made using an extended Kalman filter and a model of a nearby light source. After physical light model verification, the filter estimated surge, sway, and heading with 6 irradiance sensors and a low cost inertial measurement unit (~$15). Physical testing with video feedback suggests an average error of ~2cm in surge and sway, and ~3deg in yaw, over a 1200 cm2 operational area. This is 2-3 times better, and more consistent, than adaptations of prior art tested alongside the extended Kalman filter feedback system. The physical performance of the biomimetic platform was also tested. It has a repeatable forward velocity response with a max of 0.3 m/s and fair stability in surface testing conditions. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection