College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China.
Jiangsu Province Engineering Laboratory of Modern Facility Agriculture Technology and Equipment, Nanjing 210031, China.
Sensors (Basel). 2020 Sep 25;20(19):5484. doi: 10.3390/s20195484.
Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy, and explain its mechanism. A variety of weak classifiers classify eggs based on the spectra after preprocessing and feature wavelength extraction to obtain three classifiers with the highest accuracy. The three classifiers are used as metamodels of stacking ensemble learning to improve the highest accuracy from 96.25% to 100%. Moreover, the highest accuracy of scattering, reflection, transmission, and mixed hyperspectral of eggs are 100.00%, 88.75%, 95.00%, and 96.25%, respectively, indicating that the scattering hyperspectral for egg freshness detection is better than that of the others. In addition, the accuracy is inversely proportional to the angle of incidence, i.e., the smaller the incident angle, the camera collects a larger proportion of scattering light, which contains more biochemical parameters of an egg than that of reflection and transmission. These results are very important for improving the accuracy of non-destructive testing and for selecting the incident angle of a light source, and they have potential applications for online non-destructive testing.
散射光谱技术是一种具有许多优点的无损检测方法。在这里，我们提出了一种提高鸡蛋新鲜度准确性的方法，研究了光源入射角对准确性的影响，并解释了其机制。多种弱分类器根据预处理后的光谱和特征波长提取对鸡蛋进行分类，以获得三个准确性最高的分类器。这三个分类器被用作堆叠集成学习的元模型，将最高精度从 96.25%提高到 100%。此外，散射、反射、透射和混合光谱的鸡蛋最高精度分别为 100.00%、88.75%、95.00%和 96.25%，表明散射光谱法用于鸡蛋新鲜度检测比其他方法更好。此外，准确性与入射角成反比，即入射角越小，相机收集的散射光比例越大，其中包含的鸡蛋生化参数比反射和透射光更多。这些结果对于提高无损检测的准确性和选择光源入射角非常重要，并且在在线无损检测方面具有潜在的应用。
