Defect detection on inclined textured planes using the shape from texture method and the Delaunay triangulation

Authors:
Justin Plantier;Laurent Boutté;Sylvie Lelandais
Affiliations:
Cognitive Science Department, IMASSA, Brétigny-sur-Orge, France;CEMIF-LSC, Université d'Evry, EVRY Cedex, France;CEMIF-LSC, Université d'Evry, EVRY Cedex, France
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2002

Citing 7
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Estimation of orientation of a textured planar surface using projective equations and separable analysis with M-channel wavelet decomposition

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Abstract

We present one method for detecting defects on an inclined textured plane. This method uses a combination of a shape from texture (SFT) method with the Delaunay triangulation technique. The SFT method provides the theoretical equation of the plane orientation in two steps. First, a wavelet decomposition allows us to build an image of the inverse of the local frequency, that is the scale, that we call the local scales map. Then we perform an interpolation of this map using the equation of the theoretical variation of the scales. With the interpolation parameters it is possible to extract the texels by the use of an adaptive thresholding for each pixel of this map. Then we compute the centers of each texel in order to match a mesh on it after processing a Delaunay triangulation. When there is a defect, the regularity of the triangulation is disturbed, so one hole appears in the mesh.