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RESEARCH ARTICLE
Contents Vol 56(5)

Otolith shape contour analysis using affine transformation invariant wavelet transforms and curvature scale space representation

V. Parisi-Baradad A D , A. Lombarte B , E. Garcia-Ladona B , J. Cabestany A , J. Piera C and O. Chic B
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- Author Affiliations

A Departament d’Enginyeria Electrònica, Universitat Politècnica de Catalunya, c./ Jordi Girona 31, Barcelona 08034, Catalunya, Spain.

B Institut de Ciències del Mar (CMIMA-CSIC), Passeig Marítim 37-49, Barcelona 08003, Catalunya, Spain.

C Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya, Avgda. Canal Olimpic s/n, Castelldefels 08860, Catalunya, Spain.

D Corresponding author. Email: parisi@eel.upc.es

Marine and Freshwater Research 56(5) 795-804 https://doi.org/10.1071/MF04162
Submitted: 16 July 2004  Accepted: 7 March 2005   Published: 21 July 2005

Abstract

Fish 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.

Extra keywords: curvature scale space, fish otolith, Fourier harmonic, shape analysis, wavelet transform.


Acknowledgments

The current work was supported by the Spanish project MICYT TIC2000–0376-p4–04. The authors wish to thank Dr Wolf Arntz for his invitation to participate in the EASIZ I and II surveys. We express our gratitude to the scientific fishing teams B. Artigues, J. González and Drs E. Balgueries, A. Schröeder and R. Knust for their help during these expeditions. The authors also acknowledge B. Morales-Nin for providing the otolith images and J. M. Marquina, R. Carrillo and A. Pintor, for their help in coding the software used in this work.


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