Computer Vision Methods for Automating Turbot Fish Cutting

TL;DR

This paper presents an automated fish cutting system that uses machine vision to detect fish boundaries and define cutting curves, enabling precise head removal and fillet preparation for marketability.

Contribution

It introduces a novel integration of machine vision techniques with robotic cutting for automating turbot fish processing, which was previously manual.

Findings

Effective boundary detection using binarization and morphology

Accurate head boundary detection with Hough transform and convex hull

Successful automation of fish head cutting process

Abstract

This paper is about the design of an automated machine to cut turbot fish specimens. Machine vision is a key part of this project as it is used to compute a cutting curve for the specimen head. This task is impossible to be carried out by mechanical means. Machine vision is used to detect head boundary and a robot is used to cut the head. Binarization and mathematical morphology are used to detect fish boundary and this boundary is subsequently analyzed (using Hough transform and convex hull) to detect key points and thus defining the cutting curve. Afterwards, mechanical systems are used to slice fish to get an easy presentation for end consumer (as fish fillets than can be easily marketed and consumed).