When automatically inspecting textured surface defects, the most important step is to segment the defects from the
background. Segmentation plays a crucial role in automated visual inspection. In this study, we present a method for
segmentation of rough surface based on using texture feature derived from different illumination direction. Extract a set
of feature images that described the characteristics of the textures. Variation in illumination direction effects image
physical texture and then effects on texture segmentation. Previous studies have demonstrated that the surface
topography as a cue for image segmentation. For complicated textures, however, two rough surfaces with different
reflectance function, but similar topography must be distinguished. The images are often noisy and poor contrast.
Compared with intensity, texture is more of a global property. A method is presented that to obtain images with maximal
contrast by fusing a series of images which were acquired under different illumination directions. Using illumination
series of images contain significantly more information about the surface characteristics than single images. The
experiment result shows this is a robust and reproducible way to obtain high-contrast images containing the relevant
information for subsequent processing steps.
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