基于机器视觉技术的智能投饵方法研究

Research on intelligent bait casting method based on machine vision technology

传统的投饵机大多采用定时定量的下料方式,投饵模式相对固定,投饵系统不能根据具体的养殖情况适时调整,近年来随着海洋养殖业的不断发展,此方式已经远远不能满足养殖要求。此外,由于传统投饵机未能感知养殖对象的摄食规律及习性等因素,会造成饵料不必要的浪费及环境污染等问题,使研究高效智能化的投饵系统成为降低养殖成本的关键任务。分析养殖对象在摄食过程中的摄食规律即聚集程度及饥饱程度等,从而决定投喂量,是解决这一问题的有效途径。本文提出利用机器视觉方法对投饵过程中拍摄的水面摄食图像进行分析,提取能够反映鱼群聚集规律的特征参数,同时分析提取出图像中有鱼部分以及鱼群摄食引起的水花部分作为特征区域,将特征区域的面积比率参数作为研究鱼群摄食规律的特征参数。根据参数特征绘制随时间变化的曲线,可以直观地研究鱼群摄食规律的变化特点。根据曲线所反映的变化规律,提出了新的投饵量计算模型,并且根据摄食规律构建了一种智能化的投饵方法。对比实验研究表明,基于鱼群摄食规律研究的投饵方法使投饵过程更加符合鱼群的摄食需求,不仅节约了饵料和养殖成本,而且可降低对环境的污染。

At present, in an aquaculture environment, bait casting process of feeding machine mainly uses total time. Such feeding does not consider fish feeding regularity so it wastes bail and causes environmental pollution. High efficiency and intelligent bait casting machine system study thus becomes urgent. An effective way is to set the feeding amount through observing fish aggregation. An intelligent bait casting method based on machine vision technology is proposed in this paper Through image processing, the geometric area of the fish within the window of the camera and the ratio of the fish area to the widow area were extracted from the pictures, and were taken as characteristic parameters of the pictures. These characteristic parameters can reflect well the crowding level of the fish during the feeding process, and the variation curves of the parameters with time can represent the feeding regularity of the fish. It was also found that the parameter variation curves were similar for different fish. Based on the parameter variation curves, new bait casting scheme was designed. The advantage of using this method is it makes bait casting scientific and reasonable, not only saving feeding cost but also reducing environment pollution.