The invention provides an
otolith shape detection and identification method based on
machine learning, and relates to the technical field of
otolith detection, and the method comprises the steps: S101, obtaining an original
otolith image, and carrying out the preprocessing of the original otolith image; s102, the user marks a core
reference line on the original otolith image; s103, forming an ROI region along the core
reference line, and performing
feature extraction on the ROI region to obtain ROI region features; s104, constructing a wheel
pattern recognition model, providing prior constraints for the wheel
pattern recognition model by using an environment-wheel pattern association rule, inputting the ROI region features into the wheel
pattern recognition model, and outputting wheel pattern position information and wheel pattern number information; and S105, visualizing the position information of the wheel ripples and the number information of the wheel ripples. According to the method, the otolith
ring pattern recognition efficiency and accuracy can be improved, reliable data support can be provided for fish
population dynamic monitoring,
fishery resource evaluation and
ecological environment research, and the application range is wide.