Computer Vision Methods for Automating Turbot Fish Cutting
This work addresses a specific automation challenge in the seafood processing industry, representing an incremental application of existing methods.
The paper tackled the problem of automating turbot fish cutting by using computer vision to detect the head boundary and compute a cutting curve, enabling a robot to perform the cut and produce marketable fillets.
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).