基于机器视觉技术淡水鱼品种在线识别装置设计  

Design of the on-line identification device of freshwater fish species based on machine vision technology

作　　者：万鹏[1,2] 潘海兵[1,2] 龙长江[1] 陈红[1,2] 

机构地区：[1]华中农业大学工学院,湖北武汉430070 [2]国家大宗淡水鱼加工技术研发分中心(武汉),湖北武汉430070

出　　处：《食品与机械》2012年第6期164-167,共4页Food and Machinery

基　　金：国家自然科学基金项目(编号:61007058);中央高校基本科研业务费专项资金项目(编号:2010QC006);华中农业大学引进人才科研启动基金项目(编号:5220409079)

摘　　要：研制基于机器视觉技术的淡水鱼品种在线识别装置。采用CCD彩色摄像头、图像采集卡、光电开关、数据采集卡、输送机、照明箱等部件组成在线识别装置的硬件部分;基于Visual C++6.0平台编写具备淡水鱼图像采集、图像分析、鱼体特征提取、品种识别等功能模块的在线识别软件程序。利用本装置对鲤鱼、鲫鱼、草鱼、鳊鱼等4种大宗淡水鱼进行品种在线识别。结果表明,以BP神经网络作为识别模型,该装置对4种淡水鱼进行识别的平均准确率达到92.50%,检测所需时间平均为1.3s,该装置可以用于淡水鱼品种的在线、快速、准确识别。The on-line identification device of freshwater fish species was developed based on machine vision technology. The hardware devices of the on-line identification device were made up of CCD col- orful camera, image acquisition card, photoelectric switch, data ac quisition card, conveyer and lighting box. The software of the on- line identification device had the function module of the image acqui sition of the freshwater fish, image analysis, and feature extraction of the fish body and species identification, which was compiled by Visual C＋＋ 6.0. Four varieties bulk freshwater fish such as carp, crucian carp, grass carp, bream were identified by the device, The results show that the average accuracy rate of the identification device to four varieties freshwater fish used the BP neural network as the recognition model is about 92.50% and the required average detec- tion time is 1.3 s, the device can be used to identify the freshwater fish species on-line, rapid and accurately.

关 键 词：机器视觉技术 淡水鱼 品种 在线识别装置 设计 

分 类 号：TS254.7[轻工技术与工程—水产品加工及贮藏工程] TP391.41[轻工技术与工程—食品科学与工程]