Different approaches for condition monitoring of combustion Systems based oil the C capture and processing of flame images are presented and discussed. The objective is to devise methods capable of converting.,, geometrical luminous and, data into reliable information oil the state of practical combustion systems. suitable processing methods are needed to extract representative information from flame images. as they contain large amounts of data whose physical interpretation is not. in general, straight forward. A thorough experimental programme has been conducted in a model industrial burner. in order to create a database of flame images, for Subsequent analysis. One of the options is the extraction and analysis of representative images C features: even though the parametric studies revealed good sensitivity to changes in combustion regimes, this approach may entail some information loss and requires adaptation to the specific system. The other two methods explored are designed as flame identification techniques based oil the whole image. One of them use self-organising feature Maps and yields as Output the most probable combustion regime. among those previously characterised. The other one is an adaptation of a speech recognition method and informs about the probability of an unknown State to correspond with the different combustion regimes. Their performance was tested in terms of their success rate for identification as well as oil their capabilities to estimate NOx emission, its a representative outcome of the combustion process. Results ill other combustion situations (oil burner and premixed combustor) are also reported. The good results obtained in all cases are thought to Support the potential of the methods described for flame monitoring. (C) 2008 The Combustion Institute. Published by Elsevier Inc. All rights reserved.