农业工程学报2012，Vol.28Issue(16)：153-157,5.DOI:10.3969/j.issn.1002-6819.2012.16.024
基于机器视觉的水下鲆鲽鱼类质量估计
Weight estimation of underwater Cynoglossus semilaevis based on machine vision
摘要
Abstract
In order to solve the problem of estimating the weight of the flounder and other flatfishes underwater, the image and weight data of the tongueflsh {Cynoglossus semilaevis) were obtained at different growth stages. The area of the fish were measured through the image processing. The fitting models were established to match the area comparaed with weight. The results showed that the correlation between the area and the weight could reach at 0.9682, the average relative error was 6.17%. In addition, the weight was also affected by other shape parameters, and the ration of equivalent ellipse axes and heywood circularity factor were measured. Three-dimensional fitting models of area, ration of equivalent ellipse axes, weight, and area, heywood circularity factor, weight were established. The average relative errors of the two models were 5.50%, 5.62%, respectively. The experiment verified that the processed results of images of fish underwater obtained out of the surface and calibrated with the template underwater were consistent with that of images obtained outside the water. Consequently, the weight of flounder fish underwater can be estimated without catching the fish.关键词
水产养殖/图像处理/摄像机/半滑舌鳎/重量估计/数据拟合Key words
aquaculture, image processing, cameras, cynoglossus semilaevis, weight estimation, data fitting分类
信息技术与安全科学引用本文复制引用
王文静,徐建瑜,吕志敏,辛乃宏..基于机器视觉的水下鲆鲽鱼类质量估计[J].农业工程学报,2012,28(16):153-157,5.基金项目
浙江省重大科技攻关专项计划项目(2011C11049) （2011C11049）
宁波市自然科学基金项目(2010A610005) （2010A610005）
