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 BA 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.
Abbasi, S. , Mokhtarian, F. , and Kittler, J. (1999). Curvature scale space image in shape similarity retrieval. Springer Journal of MultiMedia Systems 7, 467–476.
| Crossref | GoogleScholarGoogle Scholar |
Friedland, K. D. , and Reddin, D. G. (1994). Use of otolith morphology in stock discriminations of Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences 51, 475–480.
Lombarte, A. , and Castellón, A. (1991). Interespecific and intraspecific otolith variability in the genus Merluccius as determined by image analysis. Canadian Journal of Zoology 69, 2442–2449.
Saito, N. , and Coifman, R. (1995). Local discriminant bases and their applications. Journal of Mathematical Imaging and Vision 5, 337–358.
| Crossref | GoogleScholarGoogle Scholar |
Torres, G. J. , Lombarte, A. , and Morales-Nin, B. (2000). Sagittal otolith size and shape variability to identify geographical intraspecific differences in three species of the genus Merluccius. Journal of the Marine Biological Association of the UK 80, 333–342.
| Crossref | GoogleScholarGoogle Scholar |
Yefanov, V. N. , and Khorevin, L. D. (1979). Distinguishing populations of pink salmon, Oncorhynchus gorbuscha, by the size of their otoliths. Journal of Ichthyology 19, 142–145.
Zahn, C. T. , and Roskies, R. Z. (1972). Fourier descriptors for plane closed curves. IEEE Transactions on Computers. Institute of Electrical and Electronics Engineers 21, 269–281.