Detection and positioning system of dead fish in factory farming
[Purpose]In factory-based circulating water breeding,excessively dense breeding environment and unstable water quality have caused water pollution and hypoxia,resulting in fish mortality.Therefore,timely detection and removal of dead fish is essential for maintaining water quality and preventing diseases from spreading.[Method]This article proposed a combination of the target detection model and the visual positioning technology of the eyes to achieve real-time detection and accurate positioning of dead fish.Firstly,the CLAHE image enhancement algorithm was used to solve the problems such as the absorption,scattering and refraction of the light facing the underwater dead fish images.Secondly,the YOLOv7-PC was built based on the YOLOv7 model.The traditional convolutional module of the high-efficiency layer aggregation network(ELAN)was replaced by a Partial Convolution(PConv)module,and a coordinate attention mechanism module was introduced into the Neck network to achieve real-time accurate detection of obscured and underwater dead fish targets.Finally,combined with the Semi-Global Block Matching(SGBM)to achieve three-dimensional positioning of underwater dead fish targets,which provided visual perception information for the salvage of dead fish robots.Taking the large-mouth black bass as an example,the accuracy and real-time performance of the YOLOv7-PC model combined with the SGBM stereo algorithm was verified by testing the video data collected at different distances.[Result]The test results showed that the accuracy,recall rate and average accuracy of the Yolov7-PC-CLAHE model proposed in the study were 97.6%,85.6%and 97.0%,respectively.The average accuracy of the comparison base YOLOv7 model had increased by 2.5%and the detection speed had increased by 31.9%.Combined with the SGBM three-dimensional algorithm algorithm could accurately perform dead fish positioning,the average relative error in the depth direction was 3.08%.[Conclusion]The method proposed in this article effectively realizes real-time detection and accurate positioning of underwater dead fish,and the algorithm's performance meets the needs of industrialized aquaculture.
image enhancementdeath fish detectionYOLOv7two-dimensional visionthree-dimensional matchingthree-dimensional positioning
NETL
NSTL
万方数据
