This thesis presents a way of automatically generating a landscape painting in the artistic style of Bob Ross. First, a relatively simple, yet effective and versatile, painting model is presented. The brushes of the painting model can be used on their own for creative applications or as a lower layer to the software components responsible for automation. Next, the brush strokes and parameters used to automatically paint eight different landscape features, each with its own adjustable attributes and randomized forms, are described. Finally, the placement of all of the automated landscape features required to achieve the layout of one of Bob Ross's landscape paintings is shown.

This thesis presents a way of automatically generating a landscape painting in the artistic style of Bob Ross. First, a relatively simple, yet effective and versatile, painting model is presented. The brushes of the painting model can be used on their own for creative applications or as a lower layer to the software components responsible for automation. Next, the brush strokes and parameters used to automatically paint eight different landscape features, each with its own adjustable attributes and randomized forms, are described. Finally, the placement of all of the automated landscape features required to achieve the layout of one of Bob Ross's landscape paintings is shown.

Research and development of Non-Photorealistic Rendering algorithms has recently moved towards the use of computer vision algorithms to extract image features. The feature representation capabilities of image moments could be used effectively for the selection of brush-stroke characteristics for painterly-rendering applications. This technique is based on the estimation of local geometric features from the intensity distribution in small windowed images to obtain the brush size, color and direction. This thesis proposes an improvement of this method, by additionally extracting the connected components so that the adjacent regions of similar color are grouped for generating large and noticeable brush-stroke images. An iterative coarse-to-fine rendering algorithm is developed for painting regions of varying color frequencies. Improvements over the existing technique are discussed with several examples.