基于图像纹理分析的大米加工等级检测方法

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%。

Rice processing level detection method based on image texture analysis

According to different processing level of rice the surface texture is different, an detection method for processing level of rice was provided. In this paper, an 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 rate of the different processing level of 4 rice samples detected with Fisher discriminant method and PNN neural network were 96.25% and 90.00%.