Hierarchical scene analysis for object recognition

David P. Casasent

doi:10.1117/12.138226

9 July 1992 Hierarchical scene analysis for object recognition

David P. Casasent

Proceedings Volume 1699, Signal Processing, Sensor Fusion, and Target Recognition; (1992) https://doi.org/10.1117/12.138226
Event: Aerospace Sensing, 1992, Orlando, FL, United States

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.

Citation Download Citation

David P. Casasent "Hierarchical scene analysis for object recognition", Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); https://doi.org/10.1117/12.138226

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