Three-dimensional target recognition from fusion of dense range and intensity images

Manuel Ramirez; Sunanda Mitra

doi:10.1117/12.50851

Three-dimensional target recognition from fusion of dense range and intensity images

Manuel Ramirez, Sunanda Mitra

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper describes an approach of feature extraction from range and intensity data for three-dimensional model-based target recognition systems. The range image of the object under study is acquired using a methodology based on a passive stereo-vision model. A coarse to fine strategy is used to explore the features in the images, and cepstral analyisis provides information about disparities between corresponding areas at each step. The surfaces of the 3-D target recovered from the passive stereo-vision model are represented by aspect graphs which are used in vector form as the input for a neural network classifier.

Original language	English
Pages (from-to)	632-637
Number of pages	6
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	1567
DOIs	https://doi.org/10.1117/12.50851
State	Published - Dec 1 1991
Event	Applications of Digital Image Processing XIV 1991 - San Diego, United States Duration: Jul 21 1991 → …

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AB - This paper describes an approach of feature extraction from range and intensity data for three-dimensional model-based target recognition systems. The range image of the object under study is acquired using a methodology based on a passive stereo-vision model. A coarse to fine strategy is used to explore the features in the images, and cepstral analyisis provides information about disparities between corresponding areas at each step. The surfaces of the 3-D target recovered from the passive stereo-vision model are represented by aspect graphs which are used in vector form as the input for a neural network classifier.

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T2 - Applications of Digital Image Processing XIV 1991

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ER -

Three-dimensional target recognition from fusion of dense range and intensity images

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