<p>The purpose of this master thesis was to study computer vision algorithms for vehicle detection in monochrome images captured by mono camera. The work has mainly been focused on detecting rear-view cars in daylight conditions. Previous work in the literature have been revised and algorithms based on edges, shadows and motion as vehicle cues have been modified, implemented and evaluated. This work presents a combination of a multiscale edge based detection and a shadow based detection as the most promising algorithm, with a positive detection rate of 96.4% on vehicles at a distance of between 5 m to 30 m. For the algorithm to work in a complete system for vehicle detection, future work should be focused on developing a vehicle classifier to reject false detections.</p>

The purpose of this master thesis was to study computer vision algorithms for vehicle detection in monochrome images captured by mono camera. The work has mainly been focused on detecting rear-view cars in daylight conditions. Previous work in the literature have been revised and algorithms based on edges, shadows and motion as vehicle cues have been modified, implemented and evaluated. This work presents a combination of a multiscale edge based detection and a shadow based detection as the most promising algorithm, with a positive detection rate of 96.4% on vehicles at a distance of between 5 m to 30 m. For the algorithm to work in a complete system for vehicle detection, future work should be focused on developing a vehicle classifier to reject false detections.

The thesis is focused on detection of local disappearance of the neural layer on retina in fundus-camera images. The first chapter describes the human eye physiology, the glaucoma disease and the analyzed data. The second chapter compares four different approaches that should enable automatic detection of a possible damage to the retinal neural layer. These four approaches have been tested and evaluated; three of them showed an acceptable correlation with the medical expert conclusions – the directional spectral approach, the edge based approach and the difference local brightness. The last approch via local co-occurrence matrices has not turned out to be informative with the respect to the issue concerned. Then a program for the automatic detection of the nerve fibre layer loss areas has been designed, realized and evaluated. This task is solved in the last chapter. A relatively good agreement between the medical expert conclusions and the conclusions detected automatically by this program has been reached.

Goal of this work is to theoretically develop and then program a system in Matlab environment to be used as a detection tool for layer of retinal neuron pathways . First part engages oneself upon the problem of analysis within spectral plane and results of using filters conceived upon statistical occurrences of certain frequencies in used samples. Second part than deals with use of gabor filters to detect neuron pathways and the statistical results gained by their use. Based on the results an analysis tool was programmed.