一种基于视觉的鱼苗体长快速非接触测量方法

A vision-based method for rapid non-contact measurement of fish length

在水产养殖过程中,及时准确地获取鱼苗形体尺寸十分重要。传统人工取样测量方式费时费力,无法满足智慧水产发展的需求。以体长分布在20~100 mm的草鱼(Ctenopharyngodon idella)鱼苗为对象,提出了一种基于视觉的鱼体体长快速测量方法,可在无参照和非接触情况下对试验鱼苗进行快速准确体长测量。首先利用RGB-D相机获取目标深度信息和灰度图像,通过图像处理完成目标鱼体与背景分割;进一步对可能存在的粘连鱼群图像提取对应的凹区域和凹点,完成基于凹点的鱼苗个体分离;然后利用改进的细化算法提取鱼体骨架,并筛选出骨架关键点;最后结合图像深度信息完成骨架点三维坐标的转换,实现鱼苗全长准确测量。结果显示,该方法对试验鱼苗全长测量的平均绝对误差为1.62 mm,平均相对误差为4.24%。研究结果可以为水产养殖业分级饲养、智能投喂等应用提供非接触测量技术支持。

It’s crucial to obtain the dimensions of fish fry accurately and quickly in aquaculture.Traditional manual sampling and measurement are time-consuming and labor-intensive and cannot meet the demands of smart aquaculture development.A vision-based method for rapid measurement of fish length is proposed for grass carp fry with length distribution from 20 to 100 mm in this paper.It allows for quick and accurate length measurement of test fish fry without reference and in a non-contact manner.Firstly,an RGB-D camera is used to capture depth information and gray images of the target.Those images are processed to segment the target fish from the background.For the case of overlapping fish,concave regions and points are extracted to separate individual fish based on concave points.An improved thinning algorithm is then used to extract the fish skeleton,and key skeleton points are selected.Finally,by combining the image depth information,the three-dimensional coordinates of the skeleton points are transformed,allowing for the accurate measurement of the total length of the fish fry.Experimental result shows that the proposed method achieves an average absolute error of 1.57 mm and an average relative error of 4.39%in the length measurement of the test fish.It provides a non-contact measurement method that supports applications such as graded feeding and intelligent feeding in the aquaculture industry.