基于图像纹理分析的大米加工等级检测方法  

Rice Processing Level Detection Method Based on Image Texture Analysis

作　　者：崔雯雯[1] 孙永海[1] 王璐[1,2] 黄碧竹 周丽聪[1] 陈方媛[1] 郭晓蕾[1] 

机构地区：[1]吉林大学生物与农业工程学院,长春130022 [2]华南理工大学轻工与食品学院,广州510640

出　　处：《中国粮油学报》2016年第6期146-149,共4页Journal of the Chinese Cereals and Oils Association

基　　金：吉林省应用基础研究(201205013);国家自然科学基金(31271861);吉林省人才开发资金

摘　　要：利用不同加工等级大米表面纹理不同的特点,提出了基于纹理分析的大米加工等级检测方法。设计了大米的计算机视觉检测系统,获取4个不同加工等级大米标准样的图像,采用灰度梯度共生矩阵的纹理分析方法提取图像的纹理特征值,采用Fisher判别法和PNN神经网络对大米加工等级进行检测判定。试验结果表明:Fisher判别法和PNN神经网络对4种不同加工等级的大米样品检测判定的正确率分别是96.25%和90.00%。Advantage of the characteristics of different surface texture processing grade rice, a detection method for processing level of rice was provided. In this paper, a computer vision detection system for processing level of rice was designed to obtain the standard rice sample images of 4 different processing levels, and then the texture features of the rice image were obtained using gray - gradient co - occurrence matrix. Afterwards, the Fisher discriminant functions constructed with stepwise discriminant analysis and PNN neural network were used to detect the processing level of the rice samples. The test results show that the average accuracy rates of the different processing levels of 4 rice samples detected with Fisher discriminant method and PNN neural network were 96.25% and 90.00%.

关 键 词：大米 加工品质 纹理 FISHER判别 

分 类 号：S233.5[农业科学—农业机械化工程]