Article ID Journal Published Year Pages File Type
84316 Computers and Electronics in Agriculture 2014 7 Pages PDF
Abstract

•A study on the usefulness of otolith weight for automated fish age classification of Atlantic cod species has been conducted.•The classification performance for multi-class support vector machines using a Atlantic cod database has been tested.•Otolith weight has been demonstrated a powerful characteristic for classification purposes.•The greatest accuracy is achieved when otolith weight is used with other features such fish length and weight.

In this paper, the discriminative capability of a combination of biological and shape features for fish age classification are analyzed. In particular, the usefulness of otolith weight in several species, in combination with other features such as otolith shape features and biological features such fish length, weight and sex is evaluated. The classification performance for different state-of-the-art statistical learning classifiers (i.e. several non-linear, non-parametric classifiers such different types of multi-class support vector machines) using an Atlantic cod database has been tested in which otolith weight has shown to be a powerful characteristic for classification purposes but the greatest accuracy is achieved when it is used simultaneously with other features.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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