Recent advances of machine vision technology in fish classification

Abstract

Abstract Automatic classification of different species of fish is important for the comprehension of marine ecology, fish behaviour analysis, aquaculture management, and fish health monitoring. In recent years, many automatic classification methods have been developed, among which machine vision-based classification methods are widely used with the advantages of being fast and non-destructive. In addition, the successful application of rapidly emerging deep learning techniques in machine vision has brought new opportunities for fish classification. This paper provides an overview of machine vision models applied in the field of fish classification, followed by a detailed discussion of specific applications of various classification methods. Furthermore, the challenges and future research directions in the field of fish classification are discussed. This paper would help researchers and practitioners to understand the applicability of machine vision in fish classification and encourage them to develop advanced algorithms and models to address the complex problems that exist in fish classification practice.