The invention provides a fish body length
estimation method and
system based on a global guidance semantic segmentation network, relates to the technical field of
computer vision and
artificial intelligence, and aims to solve the problems that in a scene that a fish body in a
monocular image and complex background interference coexist, and in a multi-fish-species mixed scene, the model segmentation generalization ability in the prior art is insufficient, and the fish body length
estimation accuracy is poor. And high-precision and robust
mask segmentation is difficult to realize. The method comprises the following steps: acquiring a fish body
monocular image, and performing
distortion correction on the fish body
monocular image; inputting the corrected fish body
monocular image into a trained global guide semantic segmentation network for semantic segmentation to obtain a semantic segmentation
mask graph of the fish body and the calibration plate, and constructing a mapping relationship between the physical size and the pixel size of the calibration plate; and performing
ellipse fitting on the semantic segmentation
mask graph of the fish body, calculating the pixel length of the fish body, and converting the pixel length of the fish body into the
actual length of the fish body. The method solves the problems in the prior art, provides the generalization ability of the
network model, and achieves the precise
estimation of the length of the fish body.