The University of Southampton
University of Southampton Institutional Repository

Colour cluster analysis for pigment identification

Martinez, Kirk and Goodall, Simon (2008) Colour cluster analysis for pigment identification At Electronic Imaging: Computer Image Analysis in the Study of Art, United States.

Record type: Conference or Workshop Item (Paper)


This paper presents image processing algorithms designed to analyse the colour CIE Lab histogram of high resolution images of paintings. Three algorithms are illustrated which attempt to identify colour clusters, cluster shapes due to shading and finally to identify pigments. Using the image collection and pigment list of the National Gallery London large numbers of images within a restricted period have been classified with a variety of algorithms. The image descriptors produced were also used with suitable comparison metrics to obtain content-based retrieval of the images.

PDF martinez.pdf - Other
Download (423kB)

More information

Published date: January 2008
Venue - Dates: Electronic Imaging: Computer Image Analysis in the Study of Art, United States, 2008-01-01
Keywords: Colour analysis, image processing, art analysis
Organisations: Web & Internet Science


Local EPrints ID: 265146
PURE UUID: 1b6500df-dd60-4395-ab85-51e2c57d8753
ORCID for Kirk Martinez: ORCID iD

Catalogue record

Date deposited: 05 Feb 2008 14:52
Last modified: 18 Jul 2017 07:29

Export record


Author: Kirk Martinez ORCID iD
Author: Simon Goodall

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.