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The work in this thesis aims at studying the problems related to the robustness of a face recognition system where specific attention is given to the issues of handling the image variation complexity and inherent limited Unique Characteristic Information (UCI) within the scope of unfamiliar identity recognition environment. These issues will be the main themes in developing a mutual understanding of extraction and classification tasking strategies and are carried out as a two interdependent but related blocks of research work. Naturally, the complexity of the image variation problem is built up from factors including the viewing geometry, illumination, occlusion and other kind of intrinsic and extrinsic image variation. Ideally, the recognition performance will be increased whenever the variation is reduced and/or the UCI is increased. However, the variation reduction on 2D facial images may result in loss of important clues or UCI data for a particular face alternatively increasing the UCI may also increase the image variation. To reduce the lost of information, while reducing or compensating the variation complexity, a hybrid technique is proposed in this thesis. The technique is derived from three conventional approaches for the variation compensation and feature extraction tasks. In this first research block, transformation, modelling and compensation approaches are combined to deal with the variation complexity. The ultimate aim of this combination is to represent (transformation) the UCI without losing the important features by modelling and discard (compensation) and reduce the level of the variation complexity of a given face image. Experimental results have shown that discarding a certain obvious variation will enhance the desired information rather than sceptical in losing the interested UCI. The modelling and compensation stages will benefit both variation reduction and UCI enhancement. Colour, gray level and edge image information are used to manipulate the UCI which involve the analysis on the skin colour, facial texture and features measurement respectively. The Derivative Linear Binary transformation (DLBT) technique is proposed for the features measurement consistency. Prior knowledge of input image with symmetrical properties, the informative region and consistency of some features will be fully utilized in preserving the UCI feature information. As a result, the similarity and dissimilarity representation for identity parameters or classes are obtained from the selected UCI representation which involves the derivative features size and distance measurement, facial texture and skin colour. These are mainly used to accommodate the strategy of unfamiliar identity classification in the second block of the research work. Since all faces share similar structure, classification technique should be able to increase the similarities within the class while increase the dissimilarity between the classes. Furthermore, a smaller class will result on less burden on the identification or recognition processes. The proposed method or collateral classification strategy of identity representation introduced in this thesis is by manipulating the availability of the collateral UCI for classifying the identity parameters of regional appearance, gender and age classes. In this regard, the registration of collateral UCI s have been made in such a way to collect more identity information. As a result, the performance of unfamiliar identity recognition positively is upgraded with respect to the special UCI for the class recognition and possibly with the small size of the class. The experiment was done using data from our developed database and open database comprising three different regional appearances, two different age groups and two different genders and is incorporated with pose and illumination image variations.

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Thesis (M.A.) (Clinical Psychology) --University of Limpopo, 2007 / The aim of this study was to determine children’s understanding of domestic violence. Children’s understanding encompasses their knowledge and perceptions of domestic violence as well as their attitude towards such violence. Three hundred (300) grade six and grade seven learners ranging in age from 11 to 16 years participated in the study. The participants included 150 girls and 150 boys. The average age of the female participants was 11 to 12 years and of the male participants the average age was 13 to 14 years. The participants resided in the Capricorn district of the Limpopo province. Participants were chosen from three regions, namely a township, city and village or farm area. A questionnaire designed by the University of Limpopo Psychology Department in conjunction with Childline Limpopo was administered to the participants. The questionnaire formed part of a broader research on children’s issues in schools. Areas covered in the questionnaire included biographical data, issues around self esteem, children’s rights, child abuse, domestic violence, gender roles and AIDS knowledge. The present study vii made use of the biographical data as well as data obtained from the domestic violence section of the questionnaire. Results indicated that 92% of participants in the sample had exposure to the concept domestic violence although only 37.3% had intimate knowledge of domestic violence victims. The source of greatest exposure to the concept was the school environment. Knowledge of domestic violence victims had a significant influence on children’s attitude towards conflict and violence. The majority of the sample did not condone violence and men were perceived as holding more violent attributes than women. The gender of the participant held no significant influence on the results. Geographic location appeared to influence responses to statements with significant differences noted by the township sample. Results of the study highlight a need to raise awareness and dispel myths regarding domestic violence. Programmes aimed at raising awareness of domestic violence should be implemented at a school level, as this is where most children are exposed to the concept. Greater awareness of organisations offering information and support to victims of violence is necessary.

Research in the development of historical understanding in students has demonstrated that the use of primary source documents engages students in a more meaningful way in the study of history (Barton, 1997c; VanSledright, 2002; Wineburg, 2001). To determine if this research was supported in a local context, I conducted a series of lessons with a class of seventh grade students using primary source documents to answer the central research question: To what extent is the development of historical understanding in students enhanced by the use of primary documents? After learning about Louis Riel and engaging with a series of primary source documents, the students used the documents to answer the question: should Louis Riel have been convicted of treason at his trial in 1885? From the class, the responses of ten participants were coded using VanSledright’s (2002) four reading strategies, ranging from comprehension strategies to more sophisticated intertextual evaluations. This case study reveals that while students struggle to work at the higher levels of historical reading, the use of primary source documents enhances student self-efficacy in social studies. This study also accentuated the need for students to be specifically taught the necessary literacy skills to decode and interpret documents in isolation and intertextually.

In this paper we introduce a novel representation of the significant changes in curvature along the bounding contour of planar shape. We call the representation the curvature primal sketch. We describe an implemented algorithm that computes the curvature primal sketch and illustrate its performance on a set of tool shapes. The curvature primal sketch derives its name from the close analogy to the primal sketch representation advocated by Marr for describing significant intensity changes. We define a set of primitive parameterized curvature discontinuities, and derive expressions for their convolutions with the first and second derivatives of a Gaussian. The convolved primitives, sorted according to the scale at which they are detected, provide us with a multi-scaled interpretation of the contour of a shape.