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Nonlinear Diffusion Filters Combined with Triangle Method Used for Noise Removal from Polygonal Shapes
Abstract
A two-step process for removing noise from polygonal shapes is presented in this chapter. A polygonal shape is represented as its turning function and then a nonlinear diffusion filter and triangle method is applied. In the first step, several different nonlinear diffusion filters are applied to the turning function that identify dominant vertices in a polygon and remove those vertices that are identified as noise or irrelevant features. The vertices in the turning function which diffuse until the sides that immediately surround them approach the same turning function are identified as noise and removed. The vertices that are enhanced are preserved without changing their coordinates, and they are identified as dominant ones. In the second step, the vertices that form the smallest area triangles are removed. Obtained experimental results demonstrate that the proposed two-step process successfully removes vertices that should be dismissed as noise while preserving dominant vertices that can be accepted as relevant features and give a faithful description of the shape of the polygon. In experimental tests of this procedure successful removal of noise and excellent preservation of shape is demonstrated thanks to appropriate emphasis of dominant vertices.
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