Open-ball-operators for 3-D object recognition
Date Issued
June 1996
Author(s)
DOI
10.1109/SOUTHC.1996.535084
Abstract
Recognition of three-dimensional objects is a crucial and challenging problem. This paper presents a method of three-dimensional object recognition using the Hopfield associative memory in neural networks. The input vectors to the Hopfield associative memory are obtained via the three-dimensional feature extraction Open-Ball operator (OBO). This approach is invariant to shift, translation, and rotation (R3) of three-dimensional objects.