基于机器视觉的大黄鱼形态参数快速检测方法  

Rapid Detecting Method for Pseudosciaena Crocea Morphological Parameters Based on the Machine Vision

作　　者：余心杰[1] 吴雄飞 王建平 陈立[1,3] 王磊[1,3] 

机构地区：[1]浙江大学宁波理工学院信息科学与工程学院,宁波315100 [2]宁波市海洋与渔业研究院,宁波315010 [3]太原科技大学电子信息工程学院,太原030024

出　　处：《集成技术》2014年第5期45-51,共7页Journal of Integration Technology

基　　金：国家自然科学基金(31201446);宁波市自然科学基金(201301A6101002);宁波市民生科技项目(2013C11026);宁波市农业重大科技攻关项目(2011C11006);宁波市科技创新团队项目(2013B82012)

摘　　要：大黄鱼形态参数测量对大黄鱼养殖遗传选育和品质改良等具有重要意义。文章结合机器视觉和称重传感器技术,设计开发了一种大黄鱼体重、体长和体宽等外部形态多参数同步自动检测系统。该系统通过机器视觉自动检测鱼体外部形态参数,通过称重传感器自动获取鱼重量参数。实验结果表明,系统的尺寸测量平均误差为0.28%,鱼重测量平均误差为0.74%,可以满足大黄鱼形态参数测量精度要求,为鱼类形态参数自动检测提供了一种有效的新途径。Morphological parameter measurement of Pseudosciaena Crocea plays an important role in its genetic selection and quality improvement. In this paper, an automatic detecting system which can measure the Pseudosciaena Crocea morphological parameters such as weight, length and body width was developed based on the machine vision and weighing sensor technology. The system can automatically detect the external morphology parameters by the machine vision, and get weight parameters through the weighing sensor. The mean errors of dimensional measurement and weighting are 0.28% and 0.74% respectively, which shows that the developed system can completely meet the requirements of morphological parameter measurement for Pseudosciaena Crocea. It is a new effective method to the automatic detection of fish morphology parameters.

关 键 词：大黄鱼 形态参数 机器视觉:图像处理 快速检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]