Abstract:
Edges are relevant information for image representation. In
this paper, we propose an algorithm for the classification of
step, concave slope, convex slope, roof, valley and staircase
edges. The importance of the classification is that it simplifies
several problems in artificial vision and image processing,
by associating specific processing rules to each type of
edge. Our classification is based on the behavioral study
of these edges with respect to differentiation operators and
scale. The first directional derivative, the gradient and the
Laplacian are used as operators. We test our algorithm on
synthetic and real grey-level images. In most cases, the classification
obtained corresponds to the intensity profile of the
image.
