Polygon detection in images

Abstract

A combination of image processing algorithms can be used to detect and extract certain objects from images. Image noise may obscure the objects in the images and must rst be removed using image denoising and smoothing methods before the extraction of image objects can e ciently be attempted. Contour detection algorithms can be used to identify and extract objects from denoised images. The type of image, noise and noise intensity will determine the e ectiveness of the denoising and smoothing methods. The combination of the aforementioned will also determine the e ciency of the contour detection algorithms. In this dissertation we give some background on basic mathematical morphology techniques and we see how those techniques are used in various image smoothers and contour detection techniques. We develop our own smoother using some ideas from other well-known smoothers and compare the performance of the di erent smoothing methods. Various contour detection algorithms are investigated and we put the combination of the smoothing methods and the contour detection algorithms to the test by comparing how e ciently they detect and extract objects from images under various conditions.