室外池塘养殖投饵系统智能控制方法研究

Research on Intelligent Control Method of Feeding System in Outdoor Breeding Pond

为解决室外池塘养殖过程中的智能化投饵难题,提出一种基于机器视觉的投饵系统智能控制方法。利用灰度共生矩阵提取熵、能量、相关性、对比度4个纹理特征参数对鱼群摄食强度进行量化评估,根据统计结果将鱼群摄食状态分为未摄食、弱摄食、强摄食3种状态;采用独立性权重法确定4个参数的最佳权重并建立参数加权融合模型。结果表明,熵的权重最高,达到47.04%,相关性的权重最低,为12.70%,能量与对比度的权重分别为27.55%、12.71%;利用支持向量机对鱼群的3种摄食状态进行识别,识别准确率达到99.77%,单帧图像处理时间为0.48s。以上方法简便快速,能够满足投饵系统智能控制的技术需求,为室外池塘养殖投饵系统的智能控制提供了一种全新思路。

In order to solve the problem of intelligent baiting in the process of outdoor pond culture,an intelligent control method of baiting system based on machine vision was proposed.4 texture feature parameters of entropy,energy,correlation and contrast were extracted from the gray-scale co-occurrence matrix to quantitatively evaluate the feeding intensity of the fish.According to the statistical results,the feeding intensity of the fish was divided into 3 types:no feeding,weak feeding and strong feeding.The independent weight method was used to determine the best weight of the 4 parameters and establish a parameter weighted fusion model.The results showed that the weight of entropy was the highest,reaching to 47.04%,the weight of correlation was the lowest with 12.70%,and the weights of energy and contrast were 27.55%,12.71%;using support vector machine to identify the 3 feeding inteisities of fish,the recognition accuracy reached 99.77%,and the processing time of a single frame image was 0.48 s.Above method was simple and fast,and could meet the technical requirements of the intelligent control of the feeding system,and provided a new idea for the intelligent control of the feeding system for outdoor pond culture.