Nowadays the development of the screen technology is really fast, there are lcd, led, oled screen and many kinds of screens. They all have their own advantages and disadvantages, LCD screen is usually constrained by the size, and the LED screen is usually constrained by the resolution. In this thesis I will introduce a tiled projection screen which combined LED and LCD together. My major work is to develop algorithms which are used to solve three major problems. The first problem is the radial distortion caused by the lens. This problem is different from the usual distortion correction problem, the method used in this thesis is a reverse process of the camera calibration and the key is to simulate the distortion formula. The second problem is the complex brightness condition of the tiled projected image. In the thesis a non-linear edge blending method is applied so the projected images could merge together seamlessly. The third problem is combination of the LED and the LCD without harming the resolution of the whole picture. The result shows that the size and the resolution have been improved greatly. / Thesis / Master of Applied Science (MASc)

The current paradigm in the lens distortion characterization industry is to use simple radial distortion models with only one or two radial terms. Tangential terms and the optimal distortion centre are also seldom determined. Inherent in the models currently used is the assumption that lens distortion is radially symmetrical. The reason for the use of these models is partly due to the perceived instability of more complex lens distortion models. This dissertation shows, in the first of its three hypotheses, that higher order models are indeed beneficial, when their parameters are determined using modern numerical optimization techniques. They are both stable and provide superior characterization. Although it is true that the first two radial terms dominate the distortion characterization, this work proves superior characterization is possible for those applications that may require it. The third hypothesis challenges the assumption of the radial symmetry of lens distortion. Building on the foundation provided by the first hypothesis, a sample of lens distortion models of similar and greater complexity to those found in literature are modified to have a radial gain, allowing the distortion corrections to vary both with polar angle and distance from the distortion centre. Four angular gains are evaluated, and two provide better characterization. The elliptical gain was the only method to both consistently improve the characterization and not ‘skew’ the corrected images. This gain was shown to improve characterization by as much as 50% for simple (single radial term) models and by 7% for even the most complex models. To create an undistorted image from a distorted image captured through a lens which has had its distortion characterized, one needs to find the corresponding distorted pixel for each undistorted pixel in the corrected image. This is either done iteratively or using a simplified model typically based on the Taylor expansion of a simple (one or two radial coefficients) distortion model. The first method is accurate yet slow and the second, the opposite. The second hypothesis of this research successfully combines the advantages of both methods without any of their disadvantages. It was shown that, using the superior characterization of high order radial models (when fitted with modern numerical optimization methods) together with the ‘side-effect’ undistorted image points created in the lens distortion characterization, it is possible to fit a ‘reverse’ model from the undistorted to distorted domains. This reverse characterization is of similar complexity to the simplified models yet provides characterization equivalent to the iterative techniques. Compared to using simplified models the reverse mapping yields an improvement of more than tenfold - from the many tenths of pixels to a few hundredths. / Dissertation (MEng)--University of Pretoria, 2009. / Electrical, Electronic and Computer Engineering / unrestricted

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Fingerprints are the most accurate and widely used biometrics for human identification due to their uniqueness, rapid and easy means of acquisition. Contact based techniques of fingerprint acquisition like traditional ink and live scan methods are not user friendly, reduce capture area and cause deformation of fingerprint features. Also, improper skin conditions and worn friction ridges lead to poor quality fingerprints. A non-contact, high resolution, high speed scanning system has been developed to acquire a 3D scan of a finger using structured light illumination technique. The 3D scanner system consists of three cameras and a projector, with each camera producing a 3D scan of the finger. By merging the 3D scans obtained from the three cameras a nail to nail fingerprint scan is obtained. However, the scans from the cameras do not merge perfectly. The main objective of this thesis is to calibrate the system well such that 3D scans obtained from the three cameras merge or align automatically. This error in merging is reduced by compensating for radial distortion present in the projector of the scanner system. The error in merging after radial distortion correction is then measured using the projector coordinates of the scanner system.

This work is focussed on different unwanted effects that damage a digitally acquired image. An image acquired using a digital camera can suffer from a series of defects. First, the noise is concerned. It occures due to discretisation. Next, there are the defects including vignetting, radial image distortion, chromatic aberration. In my thesis I also worked on backlight image compensation and panorama creation from an image sequence. For backlight images we need to increase the brightness in the dark parts of the image, so that the details became more visible. At panorama creation we are careful about brightness evenness in partial images, which is usually not conserved and consequently we try to find a suitable boundary-line to connect images and smooth it. The fundamental part of my work was writing the algorithms that are able to compensate these defects at least partly. For this aim I took use of the Matlab environment.

This thesis deals with reconstruction of golf ball position using multiple cameras. Reconstruction will be used for golf simulator project. System is using fotogrametric calibration and triangulation algorithm for obtaing point coordinates. Work also discuss options for camera selection. The result is making of prototype of the simulator.