Implementing k-Nearest Neighbor Algorithm on Scanning Aperture for Accuracy Improvement | IEEE Conference Publication | IEEE Xplore

Implementing k-Nearest Neighbor Algorithm on Scanning Aperture for Accuracy Improvement


Abstract:

Laser vision systems have demonstrated to be useful in applications for autonomous navigation, structural health monitoring, manufacturing, reverse engineering, among oth...Show More

Abstract:

Laser vision systems have demonstrated to be useful in applications for autonomous navigation, structural health monitoring, manufacturing, reverse engineering, among others. A variant of these systems are the dynamic triangulation systems, where, these vision systems consist in a positioning laser, a scanning aperture and a fixed distance between them. The positioning laser points the laser beam over the surface to scan and it is detected by the scanning aperture. The purpose of this paper is to present the principle of operation of this system, the disadvantages when taking measures at different distances, and the implementation of the k-nearest neighbor algorithm (kNN) to solve these disadvantages.
Date of Conference: 21-23 October 2018
Date Added to IEEE Xplore: 30 December 2018
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Conference Location: Washington, DC, USA

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