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8 March 1982 Multidimensional Clustering--An Application To Three-Dimensional (3D) Surface Extraction
C. M. Bjorklund, W. G. Eppler, J. J. Pearson
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Proceedings Volume 0302, Infrared Technology for Target Detection and Classification; (1982) https://doi.org/10.1117/12.932631
Event: 25th Annual Technical Symposium, 1981, San Diego, United States
Abstract
Significant development has been made in programs to analyze and display multiple vector-valued clusters of input, due in large part to the usefulness of multispectral data in remote sensing. This paper describes recent results in laser range identification of building surfaces to illustrate the general utility of such analysis/display programs. A 4-tuple of features was computed at each pixel of a range image by fitting a plane to every 5 X 5 pixel region in the image. The four plane parameters (i.e., azimuth, elevation, length of the normal vector, and residual fit error) constitute a vector image to be histogrammed and clustered. The multidimensional clusters have actual 3-D descriptions (angles in degrees, distance and residual in meters) which provide insight into the relationships within the 3-D scene, and clarifies their value in planar surface identification. Interesting cluster categories can be designed in the original image. This capability also permits visual verification of the sensitivity of the cluster choice to the results obtained.
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C. M. Bjorklund, W. G. Eppler, and J. J. Pearson "Multidimensional Clustering--An Application To Three-Dimensional (3D) Surface Extraction", Proc. SPIE 0302, Infrared Technology for Target Detection and Classification, (8 March 1982); https://doi.org/10.1117/12.932631
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KEYWORDS
Sensors
3D applications
Distance measurement
Image processing
Visualization
3D displays
3D image processing
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