为实现吸鱼泵过鱼数量的自动计数，设计了一种基于机器视觉的吸鱼泵过鱼量计数系统。该系统主要由过鱼管道、相机、光源及工业平板电脑组成；采用全遮光设计，其中过鱼管道使用透明有机玻璃材质；采用背光照射方式获取鱼类轮廓信息。围绕计数装备的工作特点，提出一种双兴趣线（Double line-of-interest, DLOI）计数方法，结合鱼类投影面积分析，构建视频切片面积变化特征。对比不同的学习算法对特征向量分类结果，选取支持向量机SVM（Support Vector Machine）算法实现过鱼数量统计。结果显示，计数系统能够实现过鱼数量统计，平均计数精度≥90%。研究表明，该计数算法能够有效区分重叠和粘连状态，有效提升了系统的鲁棒性。

In order to realize the automatic counting of the number of fish pumping through, a counting system of fish suction pump based on machine vision was designed. The system is mainly composed of fish pipe, camera, light source and industrial tablet computer. It adopts full shading design. The fish pipe is made of transparent plexiglass, and the fish contour information is obtained by backlight irradiation. Based on the working characteristics of counting equipment, a Double line-of-interest (DLOI) counting method was proposed, and the variation characteristics of video slice area were constructed by combining the analysis of projected area of fishes. By comparing the classification results of feature vectors by different learning algorithms, the SVM (Support Vector Machine) algorithm was selected to realize the counting of the number of fish pumping through. The results show that the counting system can realize the counting of the number of fish pumping through, with the average counting accuracy ≥ 90%. The counting algorithm can distinguish the overlapping and adhesion states effectively, which improves the robustness of the system.