Fish Image Segmentation Method Based on Object Detection and Edge Support

被引：0
|
作者：
Qin X. [1 ]
Huang D. [1 ,2 ]
Song W. [1 ]
He Q. [1 ]
Du Y. [1 ]
Xu H. [1 ]
机构：
[1] College of Information Technology, Shanghai Ocean University, Shanghai
[2] College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai
来源：
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | 2023年 / 54卷 / 01期
关键词：
edge support; fish images; image segmentation; object detection;
D O I：
10.6041/j.issn.1000-1298.2023.01.028
中图分类号：
学科分类号：
摘要：
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. © 2023 Chinese Society of Agricultural Machinery. All rights reserved.
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页码：280 / 286
页数：6
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