Object recognition from 2D images using Kohonen self-organized feature maps

Heba Lakany; E.G Schukat-Talamazzini; H Niemann; M.A.R Ghonaimy

Object recognition from 2D images using Kohonen self-organized feature maps

Heba Lakany, E.G Schukat-Talamazzini, H Niemann, M.A.R Ghonaimy

Biomedical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we propose an algorithm for recognition of objects from 2D images. The algorithm is neural network based. It uses Kohonen self-organised feature maps (SOFM) as a vector quantiser whose performance is compared to that of EM technique. A codebook is designed using SOFM and a simple labelling procedure is used to label the feature vectors, then the labelled training data set of di erent objects are recognised by the resilient propagation network. The algorithm is applied to 2D images of industrial objects.

Original language	English
Pages (from-to)	301-308
Number of pages	8
Journal	Pattern Recognition and Image Analysis
Volume	7
Issue number	3
Publication status	Published - 1997

Keywords

2D images
Kohonen
self organized feature maps

Cite this

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Object recognition from 2D images using Kohonen self-organized feature maps

Abstract

Keywords

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