Hierarchical clustering of RGB surface water images based on MIA-LSI approach

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dc.contributor.author Praus, Petr
dc.contributor.author Praks, Pavel
dc.date.accessioned 2010-02-22T08:07:35Z
dc.date.available 2010-02-22T08:07:35Z
dc.date.issued 2010
dc.identifier.citation Water SA. 2010, vol. 36, no. 1, s. 143-149. en
dc.identifier.issn 0378-4738
dc.identifier.issn 1816-7950
dc.identifier.uri http://hdl.handle.net/10084/78197
dc.description.abstract Multivariate image analysis (MIA) combined with the latent semantic indexing (LSI) method was used for the retrieval of similar water-related images within a testing database of 126 RGB images. This database, compiled from digital photographs of the various water levels and similar images of surface areas and vegetation, was transferred into an image matrix, and reorganised by means of principal component analysis (PCA) based on singular value decomposition (SVD). The high dimensionality of original images given by their pixel numbers was reduced to 6 principal components. Thus characterised images were partitioned into clusters of similar images using hierarchical clustering. The best defined clusters were obtained when the Ward’s method was applied. Images were partitioned into the 2 main clusters in terms of similar colours of displayed objects. Each main cluster was further partitioned into sub-clusters according to similar shapes and sizes of the objects. The clustering results were verified by the visual comparison of selected images. It was found that the MIA-LSI approach complemented with a suitable clustering method is able to recognise the similar images of surface water according to the colour and shape of floating subjects. This finding can be utilised for the automatic computer-aided visual monitoring of surface water quality by means of digital images. en
dc.language.iso en en
dc.publisher Water Research Commission en
dc.relation.ispartofseries Water SA en
dc.relation.uri http://www.wrc.org.za/Knowledge%20Hub%20Documents/Water%20SA%20Journals/Manuscripts/2010/2442.pdf en
dc.subject multivariate image analysis (MIA) en
dc.subject latent semantic indexing (LSI) en
dc.subject RGB image en
dc.subject Ward’s clustering en
dc.subject water quality en
dc.title Hierarchical clustering of RGB surface water images based on MIA-LSI approach en
dc.type article en
dc.identifier.location Není ve fondu ÚK en
dc.identifier.wos 000274194000019

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