MEPS 598:213-231 (2018)  -  DOI: https://doi.org/10.3354/meps12531

REVIEW
Digital imaging techniques in otolith data capture, analysis and interpretation

Mark Fisher1,*, Ewan Hunter2,3

1School of Computing Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
2Centre for the Environment, Fisheries and Aquaculture Sciences (CEFAS), Lowestoft, Suffolk NR33 0HT, UK
3School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
*Corresponding author:

ABSTRACT: Otoliths or ear-stones are hard, calcium carbonate structures located within the inner ear of bony fishes. Counts of rings and measurements of seasonal growth increments from otoliths are important metrics for assessment and management of fish stocks, and the preparation and microscopic analysis of otoliths forms an essential part of the routine work undertaken by fisheries scientists worldwide. Otolith analysis is a skilled task requiring accuracy and precision, but it is laborious, time-consuming to perform, and represents a significant cost to fisheries management. In the last 2 decades, several attempts to apply ‘computer vision’ (systems that perform high-level tasks and exhibit intelligent behaviour) in otolith analysis have been reported. Although considerable progress has been made and several prototype systems developed, laboratories have been reluctant to adopt image-based computer-assisted age and growth estimation (CAAGE) systems. This paper surveys applications of CAAGE, focusing on their utility for automated ageing using images of otolith macrostructure. A cost-benefit analysis of CAAGE of cod, plaice and anchovy shows that computer vision performs relatively poorly compared with morphometric techniques. However, there is evidence that information from visual features can boost the performance of morphometric CAAGE, and further work is needed to develop effective frameworks for this integrated approach. The cost benefit of these systems might be attractive to smaller laboratories that are already using age-length keys derived from otolith morphometrics for management of smaller artisanal fisheries.


KEY WORDS: Otolith · Computer-assisted age and growth estimation · CAAGE · Image analysis · Computational model


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Cite this article as: Fisher M, Hunter E (2018) Digital imaging techniques in otolith data capture, analysis and interpretation. Mar Ecol Prog Ser 598:213-231. https://doi.org/10.3354/meps12531

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