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Proceedings Paper

Hierarchical scene analysis for object recognition
Author(s): David P. Casasent
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Paper Abstract

We consider the problem of identifying each of multiple objects in a scene with object distortions and background clutter present. A unified correlator architecture is used with inference filters that hierarchically process the input image scene to perform detection, enhancement, recognition, and finally identification. The different levels of the processor use various processing techniques: hit-miss rank-order and erosion/dilation morphological filtering, distortion-invariant filtering, feature extraction, and neural net classification.

Paper Details

Date Published: 9 July 1992
PDF: 7 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138226
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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