基于BP神经网络的葡萄干分级技术的研究  

Research of Classification of Raisin Based on BP Networks

作　　者：唐晶磊[1] 景旭[1] 何东健[1] 

机构地区：[1]西北农林科技大学信息工程学院,陕西杨凌712100

出　　处：《农机化研究》2007年第11期51-53,共3页Journal of Agricultural Mechanization Research

基　　金：陕西省自然科学基金项目(2004D12)

摘　　要：为了适应农产品机器视觉分级技术的需要,通过分析葡萄干的特征参数组合对BP网络识别率的影响,确定最能反映葡萄干形态特征的参数作为等级识别的依据。为此,以BP算法为基础,采用改进的BP算法,对网络进行训练;同时,建立了基于BP神经网络葡萄干分级鉴定模型。试验结果表明,该网络分级效果较好,其平均分级准确率达到93%。In order to adapt to the primary products request of the machine vision grading technology. This article through analysis raisin characteristic parameter combination＇s influence of BP network recognition rate, and definite the parameters which could reflect the shape features perfectly. Taking the BP algorithm as the foundation, and the network was trained by improved BP; a model for accreditation raisin was presented on the basis of BP networks. Experiments verifies that this BP networks be of better results. Its classification average accuracy rate could reach 93%.

关 键 词：计算机应用 葡萄干分级 理论研究 计算机视觉 神经网络 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]