Towards making thinning algorithms robust against noise in sketch images

We introduce an adaptation framework based on scale space filtering for making thinning algorithms robust against noise in sketch images. The framework takes a sketch image as input, produces a set of Gaussian blurred images of the input sketch and uses a thinning algorithm to produce thinned versions of the blurred images. The algorithm's output is then the thinned image with the best performance measurement. Experiments using the proposed framework embedding state-of-the-art thinning algorithms show robustness against various types of noise.