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The segmentation of texture surface under varying illuminant direction

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.