The project, named "Top-Match," combined the recently developed GelSight high-resolution surface topography imaging system with state-of-the-art algorithms for matching structural features. Compared with competing technologies, this GelSight-based system is faster, less expensive, and insensitive to the optical properties of the material being measured. The project developed a robust algorithm for extracting the linear profile of aperture shear. The linear profiles can be matched as part of the matching algorithm. Researchers also demonstrated that cross-modality matching is possible. This system is able to identify known matches when scans are acquired with GelSight or Confocal scanning systems. Cross-modality matching enables labs with different technologies to share 3D data for identification. By using an open file format such as X3P, any two labs can exchange data. In 2015, the project will establish best practices and statistical performance for the system. An inter-operator variability study will be conducted. Researchers will also continue to improve the matching algorithm and shear extraction algorithm. A description of the project design encompasses materials, methods, and datasets. Settings for the dissemination of project results and progress are reported. 10 figures, 3 tables, and 3 references
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