Lab assignments for a course in Image Analysis and Computer Vision at KTH.
The first assignment in this course covers frequency analysis of image data via continuous and discrete Fourier transformations, designing smoothing filters for Gaussian convolutions, smoothing different kinds of noise via various filters and smoothing subsampled images.
The next assignment was to implement a multi scale differential geometry-based edge detector to detect lines with the Hough transform.
In the last assignment several segmentation methods were implemented and applied to images. These methods where K-means clustering, Mean-shift segmentation, Normalized Cut and Graph Cuts using image Gaussian mixture models.
