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dc.contributor.authorParisi-Baradad, Vicenç-
dc.contributor.authorLombarte, Antoni-
dc.contributor.authorGarcía-Ladona, Emilio-
dc.contributor.authorCabestany, J.-
dc.contributor.authorPiera, Jaume-
dc.contributor.authorChic, Óscar-
dc.identifier.citationMarine and Freshwater Research 56(5) 795–804 (2005)en_US
dc.description10 pages, 9 figures, 3 tablesen_US
dc.description.abstractFish otolith morphology has been closely related to landmark selection in order to establish the most discriminating points that can help to differentiate or find common characteristics in sets of otolith images. Fourier analysis has traditionally been used to represent otolith images, since it can reconstruct a version of the contour that is close to the original by choosing a reduced set of harmonic terms. However, it is difficult to locate the contour’s singularities from this spectrum. As an alternative, wavelet transform and curvature scale space representation allow us to quantify the irregularities of the contour and determine its precise position. These properties make these techniques suitable for pattern recognition purposes, ageing, stock determination and species identification studies. In the present study both techniques are applied and used in an otolith classification system that shows robustness against affine image transformations, shears and the presence of noise. The results are interpreted and discussed in relation to traditional morphology studies.en_US
dc.description.sponsorshipThe current work was supported by the Spanish project MYCYT TIC2000-0376-P4-04.en_US
dc.format.extent22195 bytes-
dc.publisherCSIRO Publishingen_US
dc.subjectCurvature scale spaceen_US
dc.subjectFish otolithen_US
dc.subjectFourier harmonicen_US
dc.subjectShape analysisen_US
dc.subjectWavelet transformen_US
dc.titleOtolith shape contour analysis using affine transformation invariant wavelet transforms and curvature scale space representationen_US
dc.description.peerreviewedPeer revieweden_US
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