Depictions of Thailand in Australian and Thai writings:Reflections of the Self and Other

This thesis offers both an examination of the depiction of Thailand in Australian novels, short stories and poems written in the 1980s and after, and an analysis of modern Thai novels and short stories that reflect similar themes to those covered in the Australian literature. One Australian film is also examined as the film provides an important framework for the analysis of some of the short stories and novels under consideration. The thesis establishes a dialogue between Thai and Australian literatures and demonstrates that the comparison of Australian representations of Thailand with Thai representations challenges constructively certain dominant political and social ideologies that enhance conservatism and the status quo in Thailand. The author acknowledges that the discussion of the representations of Thailand in contemporary Australian novels and short stories needs to take into account the colonial legacy and the discourse of Orientalism that tends to posit the ‘East’ as the ‘West’’s ‘Other’. Textual analysis is thus informed by post-colonial and cross-cultural theories, starting from Edward Said’s powerful and controversial critique of Western representation of the East in Orientalism. The first part of the thesis examines Australian crime stories and shows how certain Orientalist images and perceptions persist and help reinforce the image of the East and its people as the antithesis of the West. From Chapters Three through Six, however, more literary works by Australian authors are examined. The important finding is that most of the Australian authors under consideration attempt, though not always successfully, to resist and challenge the Eurocentric stereotypes of Asia and Asians that dominated Australian literature in earlier periods. This difference between contemporary Australian authors and their predecessors seems to reflect modern Australia’s endeavor to distinguish itself from the rest of the Western world and to redefine its relationship with Asia. As literary representations cannot be separated from socio-political contexts, the thesis also includes discussion of the Thai social and political history and, where appropriate, shows how colonialism and neo-colonialism exert their impact on modern Thailand

Expression and prognostic value of Wilms' tumor 1 and early growth response 1 proteins in nephroblastoma

Wilms' tumor is one of the most common solid tumors of children. The protein product of the tumor-suppressor gene, Wilms' tumor 1 (WT-1), binds to the same DNA sequences as the protein product of the early growth response 1 (EGR-1) gene. There is experimental evidence that EGR-1 is involved in controlling cell growth. The expression of both genes in Wilms' tumor was studied by others, mainly at the mRNA level. The present study evaluates the prognostic value of WT-1 and EGR-1 in 61 Wilms' tumors of chemotherapeutically treated patients at the protein level, using an immunohistochemical approach. WT-1 was expressed in normal kidney tissues and in the blastemal and epithelial component of Wilms' tumor, whereas stromal tissue was negative. EGR-1 was expressed in normal kidney tissues and in the three main cell types of Wilms' tumor. In 59 and 56% of Wilms' tumor, the blastemal cells stained for WT-1 and EGR-1, respectively. The blastemal expression of WT-1 and EGR-1 and the epithelial expression of WT-1 were statistically significantly correlated with clinical stage. WT-1 immunoreactivity correlated with EGR-1 expression. Univariate analysis showe

Random sampling methods for two-view geometry estimation

This thesis treats efficient estimation algorithms for the epipolar geometry, the model underlying two views of the same scene or object. The epipolar geometry is computed from image correspondences that are found by local feature matching. These correspondences are used to calculate the fundamental matrix, which is the mathematical representation of the epipolar geometry. Since there are outliers among the correspondences, the fundamental matrix is usually calculated by the robust RANSAC (RANdom SAmple Consensus) algorithm which is very well suited for this purpose. A disadvantage of the algorithm, however, is that it shows a considerable complexity for higher outlier ratios. This hampers its application in vision algorithms dealing with many views. In this thesis we investigate techniques for faster fundamental matrix estimation using RANSAC. The first approach that is taken is the computation of inlier probabilities for the correspondences, that are used during sampling in the RANSAC algorithm to stimulate the selection of inliers. The second approach is the reduction of the required number of RANSAC samples by the selection of fewer correspondences per sample. The fundamental matrix hypotheses are then completed using the remaining correspondences.Electrical Engineering, Mathematics and Computer Scienc

Image enhancement for noisy color imagery

Recently new techniques for night vision cameras are developed. So-called EMCCD cameras are able to record color information about the scene. However, in low-light situations this imagery becomes noisy. This is also the case for normal CCD cameras in dark situations or in shadowed areas. In this paper we present image enhancement techniques for noisy color imagery. The techniques are based on grey-value image enhancement techniques, in particular dynamic super-resolution reconstruction, which is used to enhance the lightness of the image, and local adaptive contrast enhancement. With the super-resolution technique the temporal noise in the lightness channel of the imagery is removed. The color information of the images is spatially filtered using the edge information of the enhanced lightness image. The result is colored output imagery with reduced temporal nois

Complex threat detection: Learning vs. rules, using a hierarchy of features

Theft of cargo from a truck or attacks against the driver are threats hindering the day to day operations of trucking companies. In this work we consider a system, which is using surveillance cameras mounted on the truck to provide an early warning for such evolving threats. Low-level processing involves tracking people and calculating motion features. Intermediate-level processing provides kinematics and localisation, activity descriptions and threat stage estimates. At the high level, we compare threat detection performed with a statistical trained SVM based classifier against a rule based system. Results are promising, and show that the best system depends on the scenario

Local Adaptive Contrast Enhancement for Color Images

A camera or display usually has a smaller dynamic range than the human eye. For this reason, objects thatcan be detected by the naked eye may not be visible in recorded images. Lighting is here an important factor; improper local lighting impairs visibility of details or even entire objects. When a human is observing a scene with different kinds of lighting, such as shadows, he will need to see details in both the dark and light parts of the scene. For grey value images such as IR imagery, algorithms have been developed in which the local contrast of the image is enhanced using local adaptive techniques. In this paper, we present how such algorithms can be adapted so that details in color images are enhanced while color information is retained. We propose to apply the contrast enhancement on color images by applying a grey value contrast enhancement algorithm to the luminance channel of the color signal. The color coordinates of the signal will remain the same. Care is taken that the saturation change is not too high. Gamut mapping is performed so that the output can be displayed on a monitor. The proposed technique can for instance be used by operators monitoring movements of people in order to detect suspicious behavior. To do this effectively, specific individuals should both be easy to recognize and track. This requires optimal local contrast, and is sometimes much helped by color when tracking a person with colored clothes. In such applications, enhanced local contrast in color images leads to more effective monitorin

Super-resolution of faces using the epipolar constraint

In this paper we present a super-resolution scheme specifically designed for faces. First, a face detector is used to find faces in a video frame, after which an optical flow algorithm is applied to track feature points on the faces. Given the set of flow vectors corresponding to a single face, we propose to use the epipolar geometry for rejecting outlying flow vectors. This will improve the registration of the face over multiple frames, and thus lead to an improved super-resolution image. An iterative backprojection method is used for acquiring the super-resolution image

Re-identification of persons in multicamera surveillance under varying viewpoints and illumination

The capability to track individuals in CCTV cameras is important for surveillance and forensics alike. However, it is laborious to do over multiple cameras. Therefore, an automated system is desirable. In literature several methods have been proposed, but their robustness against varying viewpoints and illumination is limited. Hence performance in realistic settings is also limited. In this paper, we present a novel method for the automatic re-identification of persons in video from surveillance cameras in a realistic setting. The method is computationally efficient, robust to a wide variety of viewpoints and illumination, simple to implement and it requires no training. We compare the performance of our method to several state-of-the-art methods on a publically available dataset that contains the variety of viewpoints and illumination to allow benchmarking. The results indicate that our method shows good performance and enables a human operator to track persons five times faster

Ship recognition for improved persistent tracking with descriptor localization and compact representations

For maritime situational awareness, it is important to identify currently observed ships as earlier encounters. For example, past location and behavior analysis are useful to determine whether a ship is of interest in case of piracy and smuggling. It is beneficial to verify this with cameras at a distance, to avoid the costs of bringing an own asset closer to the ship. The focus of this paper is on ship recognition from electro-optical imagery. The main contribution is an analysis of the effect of using the combination of descriptor localization and compact representations. An evaluation is performed to assess the usefulness in persistent tracking, especially for larger intervals (i.e. re-identification of ships). From the evaluation on recordings of imagery, it is estimated how well the system discriminates between different ships