基于机器视觉的花生品种识别系统研究  

Research on Peanut Species Identification System Based on Computer Vision

作　　者：邓立苗[1] 韩仲志[1] 于仁师[1] 

机构地区：[1]青岛农业大学理学与信息科学学院,山东青岛266109

出　　处：《农机化研究》2013年第8期166-169,共4页Journal of Agricultural Mechanization Research

基　　金：山东省自然科学基金项目(ZR2010CM039)

摘　　要：为了实现花生品种自动识别,收集了12个花生品种的600粒籽仁作为实验样本,利用计算机视觉和图像处理技术对图像进行处理;然后,对每幅样本图像提取形态、颜色和纹理等3大类共48个特征,建立人工神经网络(ANN)和支持向量机(SVM)识别模型对这些特征进行分析识别,并基于Visual C++6.0环境构建识别系统。运行结果表明,SVM方法识别效果比较稳定,对12个花生品种自我识别率达到100%,测试识别率达到83%;另外,基于Visual C++的识别系统在识别效果与效率方面比Matlab都有了较大的提高。该花生品种识别系统对于花生品种识别具有积极意义。Based on image processing and computer vision technology,we obtained 600 images of 12 varieties,Among which We take 45 images as training sample images,and the remaining 5 as test images.For each image,we have acquired 48 characteristics.Then we constructed the artificial neural network models and support vector machine model to identify different species based on Visual C＋＋6.0.Results show that the recognition effect of the SVM method is more stability and the overall self-recognition performance can reach 100%.At the same time,recognition system based on Visual C＋＋ has better recogniton effect and higher efficiency than the system based on Matlab.Methods and conclusions of this paper have positive significance to the detection of Peanut varieties.

关 键 词：花生 图像处理 支持向量机 VISUAL C++ 机器视觉 

分 类 号：S126[农业科学—农业基础科学] TP391[自动化与计算机技术—计算机应用技术]