Bergasa, L and Duffy, N and Lacey, Gerard and Mazo, M (2000) Industrial inspection using Gaussian functions in a colour space. Image and Vision Computing, 18 (12). pp. 951-957. ISSN 02628856

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Abstract

This paper presents an original method of modelling the colour distributions of images using 2D Gaussian functions and its application to flaw detection in industrial inspection. 2D Gaussian functions are used to model the colours that appear in the non-flawed images in an unsupervised manner. Pixels under test are compared to the colour distribution from training images. 140 images have been tested and the results are given. This method has a wide range of applications for detecting colour separable objects in images. It also has great potential in industrial inspection due to its speed, accuracy and unsupervised training.

Item Type:	Article
Keywords:	Colour object detection; Gaussian functions; Colour clustering; Competitive learning histogram; Automated industrial inspection;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	16905
Identification Number:	https://doi.org/10.1016/S0262-8856(00)00035-4
Depositing User:	Gerard Lacey
Date Deposited:	31 Jan 2023 14:38
Journal or Publication Title:	Image and Vision Computing
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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