An approach to three-dimensional object recognition using a hybrid Hopfield network

Author

Brooks, Timothy D. ; Kim, Jung H.

Author_Institution

Dept. of Electr. Eng., North Carolina A&T State Univ., Greensboro, NC, USA

fYear

1993

fDate

7-9 Mar 1993

Firstpage

540

Lastpage

544

Abstract

A hybrid Hopfield network previously used to solve two-dimensional occluded object recognition problems is adapted to the three-dimensional problem. It is assumed that feature extraction has yielded a set of vertices for the model and a set of vertices for the input object. From these vertices local and relational features are obtained for use in a hybrid Hopfield network graph-matching algorithm used to realize three-dimensional single-input object recognition

Keywords

Hopfield neural nets; convergence; feature extraction; fuzzy neural nets; multidimensional systems; object recognition; relational algebra; feature extraction; graph-matching algorithm; hybrid Hopfield network; local features; occluded object recognition; relational features; three-dimensional object recognition; Data mining; Equations; Feature extraction; Fuzzy neural networks; Impedance matching; Maintenance; Neural networks; Object recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, 1993. Proceedings SSST '93., Twenty-Fifth Southeastern Symposium on

Conference_Location

Tuscaloosa, AL

ISSN

0094-2898

Print_ISBN

0-8186-3560-6

Type

conf

DOI

10.1109/SSST.1993.522839

Filename

522839

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3233792