适用于水质污染判别的鱼体尾频检测模型A fish tail frequency detection model applied to water quality pollution identification
赵锋,刘茹,彭红梅,严升,高强
摘要(Abstract):
为了实时准确地检测视频中运动鱼体的尾频特征,提出基于鱼体关键特征点的尾频检测模型。通过计算机视觉图像处理算法得到鱼体的二值图像,根据鱼体形体特征及摆尾特征,鱼体质心、尾点、头点等特征点坐标建立鱼体摆尾角度几何模型。最后通过对连续视频帧内鱼体摆尾角度分析,得到鱼体摆尾频率的变化规律。实验结果表明,该模型能够实时有效地获取单帧图像中鱼体摆尾特征,且在p H=7(水质正常)、p H=5(水质异常)、p H=3(水质恶化)三种水质中的鱼体尾频测试结果与实验观测到的尾频变化规律相符合,处理每帧图像平均耗时93.6 ms,满足系统实时性要求。
关键词(KeyWords): 水质污染;鱼体;尾频;特征点;计算机视觉;变化规律
基金项目(Foundation): 陕西省科技统筹创新工程计划资助项目(2016KTCQ01-26);; 西安市科技计划项目:兰环智慧环保云及公共服务平台研发2017084CG/RC047(XAYD004);; 2018年度陕西省教育厅服务地方专项:无线智能节水灌溉系统的研制及应用(2018JYT029)~~
作者(Author): 赵锋,刘茹,彭红梅,严升,高强
DOI: 10.16652/j.issn.1004-373x.2018.15.012
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