Abstract
The effectiveness of colour spaces for the encapsulation of multivariate and distributed source information has led to increasing interest in their deployment in industrial monitoring technology. Other advantageous features are the availability of several hardware technologies that allow early transformation of a variety of monitored quantities into colour information, the compression of data at an early stage, and the familiarity of colour as a means for human assimilation of quantitative information.
To fully realise the potential of colour space representation for enhancing information gathering and enrichment demands its integration with the data mining process. In monitoring applications this must include a capacity for real-time distributed processing and delivery. This contribution describes the relevant characteristics of the representation of information in colour spaces and some of the ways in which it is being combined with data mining methods to develop industrial monitoring solutions. These are illustrated by particular examples from the energy and manufacturing industries of clustering, visualisation and statistical analysis for colour space information.
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Brazier, K.J., Deakin, A.G., Cooke, R.D., Russell, P.C., Jones, G.R. (2001). Colour Space Mining For Industrial Monitoring. In: Braha, D. (eds) Data Mining for Design and Manufacturing. Massive Computing, vol 3. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4911-3_16
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DOI: https://doi.org/10.1007/978-1-4757-4911-3_16
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