Self-affine mapping system and its application to object contour extraction

A self-affine mapping system which has conventionally been used to produce fractal images is used to fit rough lines to contours. The self-affine map’s parameters are detected by analyzing the blockwise self-similarity of a grayscale image using a simplified algorithm in fractal encoding. The phenomenon that edges attract mapping points in self-affine mapping is utilized in the proposed method. The boundary of the foreground region of an alpha mask is fitted by mapping iterations of the region. It is shown that the proposed method accurately produces not only smooth curves but also sharp corners, and has the ability to extract both distinct edges and blurred edges using the same parameter. It is also shown that even large gaps between the hand-drawn line and the contour can be fitted well by the recursive procedure of the proposed algorithm, in which the block size is progressively decreased. These features reduce the time required for drawing contours by hand.