CN111428677B - 无人机自动监测海上网箱养殖鱼类水面环游状态的方法 - Google Patents
无人机自动监测海上网箱养殖鱼类水面环游状态的方法 Download PDFInfo
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Abstract
本发明公开一种无人机自动监测海上网箱养殖鱼类水面环游状态的方法,将流体示踪测量中的PIV技术融入到鱼群运动分析中,将鱼类作为水面流动的示踪颗粒,同时在考虑无人机拍摄图像角度存在变化的基础上对所采集图像进行校正并通过不同时间、不同空间的图像帧近邻互相关联分析,获取网箱内的运动矢量场及其养殖鱼类水面环游规律程度,从而判断海上网箱养殖鱼类水面环游状态,进而确定鱼类养殖是否出现异常。本发明以视觉感知代替人工的视频分析,省时省力,大幅度地提高无人机海上养殖状态监测的效率。
Description
技术领域
本发明属于海上网箱养殖监测领域,尤其是一种无人机自动监测海上网箱养殖鱼类水面环游状态的方法。
背景技术
目前,海上网箱养殖河鲀等鱼类较为普遍,需要在养殖过程中对养殖鱼类的水面环游状态进行监测,以便及时发现异常并进行相应的处理。现有的监测方法是由无人机根据GPS点位飞到指定目标区域并通过设置在机身上的摄像头采集多帧海上网箱养殖现场的俯视图像,之后依靠人工对无人机采集的图像(视频)分析以获得养殖鱼类水面环游状态,当养殖鱼类在水面是按规律环游时,则养殖正常,反之养殖鱼类在水面运动较为杂乱时,则养殖异常。人工分析费时费力,效率低。
发明内容
本发明是为了解决现有技术所存在的上述技术问题,提供一种无人机自动监测海上网箱养殖鱼类水面环游状态的方法。
本发明的技术解决方案是:一种无人机自动监测海上网箱养殖鱼类水面环游状态的方法,依次按照如下步骤进行:
a. 按照设定的GPS点位路径在海上网箱养殖现场进行巡检飞行;
b. 以设置在机身上的摄像头采集多帧海上网箱养殖现场的俯视图像;
c. 将所采集的海上网箱养殖现场的俯视图像当前帧进行二值化处理;
d. 对二值图像进行反色处理后识别网箱内部区域,并将网箱内部区域作为ROI区域Img1;
e. 对网箱边框进行特征提取,确定至少4个不共线的特征点坐标;
f. 使用特征匹配法在所采集的前一帧图像中寻找与步骤e所得特征点相对应的位置,形成至少4个特征点对并计算特征点对之间的仿射变换参数,按照仿射变换参数将t时刻图像的ROI区域Img1映射到t-1时刻图像坐标平面上,得到ROI区域图像Img2;
g. 按PIV粒子图像测速算法对图像Img2和图像Img1进行互相关联匹配分析,得到ROI区域内的运动矢量场;
h. 以ROI区域内的运动矢量场每个矢量线j为中心矢量线, j=1,2,3…m,m为中心矢量线的数量,分别以每个中心矢量线位置为中心,以R为半径形成区域Wn,计算区域Wn内所有矢量线i的方向与中心矢量线方向之间的差值,i=1,2,3…n,所述n为区域Wn内除中心矢量线外其他矢量线的数量,对差值/>取绝对值进行累加并求平均,得到该位置的差异均值/>,遍历所有中心矢量线计算/>,得到/>,当V大于阈值T时,则海上网箱养殖鱼类水面环游状态存在异常,反之则海上网箱养殖鱼类水面环游状态正常。
本发明将流体示踪测量中的PIV(Particle Image Velocimetry)技术融入到鱼群运动分析中,将鱼类作为水面流动的示踪颗粒,同时在考虑无人机拍摄图像角度存在变化的基础上对所采集图像进行校正并通过不同时间、不同空间的图像帧近邻互相关联分析,获取网箱内的运动矢量场及其养殖鱼类水面环游规律程度,从而判断海上网箱养殖鱼类水面环游状态,进而确定鱼类养殖是否出现异常。本发明以视觉感知代替人工的视频分析,省时省力,大幅度地提高无人机海上养殖状态监测的效率。
具体实施方式
本发明的无人机自动监测海上网箱养殖鱼类水面环游状态的方法,依次按照如下步骤进行:
a. 按照预先设定的GPS点位路径在海上网箱养殖现场进行巡检飞行;
b. 以设置在机身上的摄像头采集多帧海上网箱养殖现场的俯视图像,并将图像通过无线网络传输到远程数据处理机中等待处理;
c. 采用OSTU法将所采集的海上网箱养殖现场的俯视图像当前帧进行自适应二值化处理;
d. 二值化处理后的图像中网箱边框为白色、水面为黑色,再对二值图像进行反色处理,按面积和形状特征识别网箱内部区域,并将网箱内部区域作为ROI区域Img1;
e. 对网箱边框进行特征提取,可采用Harris角点检测法获取方形养殖网箱的四个角点作为特征点,即确定至少4个不共线的特征点坐标;
f. 使用特征匹配法在所采集的前一帧图像中寻找与步骤e所得特征点相对应的位置,形成至少4个特征点对并计算特征点对之间的仿射变换参数,按照仿射变换参数将t时刻图像的ROI区域Img1映射到t-1时刻图像坐标平面上,得到ROI区域图像Img2;
g. 按PIV粒子图像测速算法对图像Img2和图像Img1进行互相关联匹配分析,得到ROI区域内的运动矢量场;
Claims (1)
1.一种无人机自动监测海上网箱养殖鱼类水面环游状态的方法,其特征在于依次按照如下步骤进行:
a. 按照设定的GPS点位路径在海上网箱养殖现场进行巡检飞行;
b. 以设置在机身上的摄像头采集多帧海上网箱养殖现场的俯视图像;
c. 将所采集的海上网箱养殖现场的俯视图像当前帧进行二值化处理;
d. 对二值图像进行反色处理后识别网箱内部区域,并将网箱内部区域作为ROI区域Img1;
e. 对网箱边框进行特征提取,确定至少4个不共线的特征点坐标;
f. 使用特征匹配法在所采集的前一帧图像中寻找与步骤e所得特征点相对应的位置,形成至少4个特征点对并计算特征点对之间的仿射变换参数,按照仿射变换参数将t时刻图像的ROI区域Img1映射到t-1时刻图像坐标平面上,得到ROI区域图像Img2;
g. 按PIV粒子图像测速算法对图像Img2和图像Img1进行互相关联匹配分析,得到ROI区域内的运动矢量场;
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