New method for sensor data fusion in machine vision

Yuan-Fang Wang

doi:10.1117/12.49973

1 September 1991 New method for sensor data fusion in machine vision

Yuan-Fang Wang

Proceedings Volume 1570, Geometric Methods in Computer Vision; (1991) https://doi.org/10.1117/12.49973
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

In this paper, we propose a new scheme for sensor data fusion in machine vision. The proposed scheme uses Kalman filter as the sensor data integration tool and hierarchical B- spline surface as the recording data structure. Kalman filter is used to obtain statistically optimal estimations of the imaged surface structure based on external sensor measurements. Hierarchical B-spline surface maintains high-order surface derivative continuity, may be adaptively refined, possesses desirable local control property, and is storage efficient. Hence, it is used to record the reconstructed surface structure.

Citation Download Citation

Yuan-Fang Wang "New method for sensor data fusion in machine vision", Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); https://doi.org/10.1117/12.49973

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