computer vision

Image stitching is the process of combining several images of a scene taken from approximately the same viewpoint but at different angles to create a larger resulting image. One of the underlying assumptions of this process is that the fields of view of the images to be stitched slightly overlap. This assumption allows for the detection of common features within the images. The relative positions of the features allows for the calculation of a matrix transformation which describes how to warp one image to fit the coordinate system of another....

The following are a few of the most interesting projects completed for the Intro to Computer Vision course which implement several basic computer vision tasks. The results seen in each of these reports were produced by implementing the relevant algorithms from scratch using NumPy. OpenCV was only used for loading images or drawing on top of images. Canny Edge Detection The purpose of this project was to implement the Canny Edge detection algorithm which consists of 5 main steps: gaussian smoothing, calculating the image gradient, selecting thresholds for the gradient magnitude, thinning the gradient magnitudes by suppressing non-maxima, and finally, linking strong edges along weaker edges....