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作 者:刘泽 谭彬 刘怡然 LIU Ze;TAN Bin;LIU Yiran(College of Information Science and Engineering,Shanxi Agricultural University,Jinzhong 030801)
机构地区:[1]山西农业大学信息科学与工程学院,晋中030801
出 处:《计算机与数字工程》2025年第3期835-839,共5页Computer & Digital Engineering
基 金:山西农业大学青年科技创新基金项目(编号:2019025);山西农业大学信息科学与工程学院“教研管”基金项目(编号:XK19204)资助。
摘 要:随着视频监控在水产品养殖生产中应用的不断深入,计算机视觉技术无接触、自动化的特点对鱼类养殖健康化、规模化发展产生重要作用。然而,高密度的集约化养殖中,一旦出现病鱼、死鱼很容易造成病菌快速传染和水质迅速恶化,导致鱼类大规模生病和死亡。为了保障循环水养殖池的水质健康,提出了基于图像分割的循环水养殖鲽形目死鱼识别方法。首先基于同态滤波方法预处理图像,然后,基于颜色阈值的图像分割算法提取前景,最后基于改进形状特征的识别方法对死鱼进行识别。在循环水养殖工厂采集图片并进行了实验,结果表明,该方法能有效排除图片中光线暗淡、水面反光、浮沫等图片质量的影响,达到自动迅速识别养殖池中死鱼的目的。With the continuous deepening of the application of video surveillance in aquatic product aquaculture production,non-contact and automatic computer vision technology plays an essential role in the healthy and large-scale development of fish rearing.The flatfish aquaculture facility has driven the development of seawater-recirculating factory aquaculture.However,in high-density intensive farming,it is easy to cause rapid infection of bacteria and rapid deterioration of water quality once sick and dead fish appear,resulting in large-scale disease and death of fish.In order to ensure the water quality in recirculating aquaculture ponds,an image segmentation-based method for identifying dead fish in recirculating aquaculture ponds is proposed.Firstly,the image is preprocessed based on the homomorphic filtering method,then the image segmentation algorithm based on the color threshold is used to extract the foreground,and finally,the dead fish is identified based on the improved shape feature recognition method.The pictures are collected in the recirculating aquaculture factory and the experiment is carried out.The results show that this method could effectively eliminate the influence of the picture quality such as dim light,reflection on the water surface,and floating foam in the pictures,achieving the purpose of automatically and quickly identifying the dead fish in the aquaculture ponds.
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