Surface Extraction Using Spatial Position From Line Drawings

Line drawings can be obtained from digital images using a combination of various edges processing techniques such as edge detection, edge thinning, perceptual organization, the Hough transform, and others. Our interest has been the extraction of surfaces for use in subsequent object recognition algorithms. An initial step of the surface extraction process can yield an edge image that allows detection of viewpoint invariant properties of the edge such as symmetry, collinearity, curvilinearity, parallelism, and co-termination. These properties contribute to the determination of the surfaces making up an object. Additionally, surface extraction from line drawings is a very important sub-system of computer vision in the area of 3-D object recognition. Curent approaches of the surface extraction require a pre-defined data structure of the vertice and edge of an object. Using the data structure, all edge directions are taken clockwise, thus if the edge is counted twice with different directions, the edge is considered as the common edge of two different surfaces. Consequently, the computation cost is very high and increases tremendously for complex objects. In this paper, we propose a very simple algorithm to extract both whole (bounding) and component surfaces. Our approach is based on the spatial position of contours without any geometric constraints. The approach locates boundaries of lines in an image that are easily measured by a city-block distance transformation. The surface is then obtained by peeling off the outside boundary of the contour. The component surfaces are then separated by the set of inside boundaries, if present