As such, it is well known that not every detail of an object’s surface is noticeable in a single image. The shading and shadows on its surface typically change as a result of the orientation of the surface in relation to a light source, as well as the properties of the incoming light. Photometric stereo theoryĬonsider a uniformly-colored object. However, photometric stereo computational imaging techniques that combine images obtained with varying directional illumination and analyze the resulting reflections from those images are an effective means of producing images with enhanced contrast. The challenge of generating enough contrast in these situations is formidable. Such features can rise from or recess into a surface, or have a different coating or texture compared to the rest of the surface while still having the same appearance, color-wise, as the rest of the surface. ARNAUD LINA, PIERANTONIO BORIERO, and KATIA OSTROWSKIĪ key challenge in machine vision applications is generating images with sufficient contrast to reliably discern objects or features of interest-such as defects or symbols-from the general background. By combining images obtained with varying directional illumination and analyzing the reflections, photometric stereo is an effective computational imaging technique to enhance image contrast.
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