Computer Microvision Even after magnification by a light microscope, the sound-induced motions of inner ear structures are small compared to the pixel spacing of a modern CCD camera. To obtain quantitative estimates of these subpixel displacements, we apply algorithms from computer vision. Some computer vision algorithms provide more accurate estimates of subpixel displacements than others. This figure and the associated video illustrates two widely-used algorithms. We have shown that these algorithms are actually equivalent in the sense that they produce exactly the same displacement estimates given the same input data.
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We have developed new computer vision algorithms that provide more accurate displacement estimates. Using the new algorithms, we can resolve displacements as small as 4 nm using light microscopy. Unlike electronics, simple methods for testing and characterizing internal failure modes of MEMS do not exist. For the designer, it can result in large numbers of costly prototypes. For the fabricator, it means reduced yields because common techniques such as laser trimming cannot be applied.