Segmenting fish objects from images is a key step in extracting fish biological information. In view of the low accuracy of current methods in fuzzy underwater fish image segmentation, a fish image segmentation method based on object detection and edge support was proposed. Firstly, the fish objects were cut out from the image by using the method of object detection, and the whole image segmentation was transformed into region segmentation. Then, the edge support method was used to segment the fish in the region, so as to further improve the segmentation accuracy of the model. The experimental results showed that the segmentation accuracy of the method was 81.75%, 83.73% and 85.66%, respectively by the models with VGG-16, ResNet-50 and ResNet-101 as the backbone network. The segmentation accuracy of the model with ResNet-101 as the backbone network was 14.24 percentage points, 11.36 percentage points and 9.45 percentage points higher than that of Mask R-CNN, U-Net and DeepLabv3 models, respectively. The method can be applied to the automatic extraction of fish biological information.