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ondestructive Detection for Egg Freshness Based on Hyperspectral Scattering Image Combined with Ensemble Learning
Sensors ( IF 3.9 ) Pub Date : 2020-09-25 , DOI: 10.3390/s20195484
Dejian Dai , Tao Jiang , Wei Lu , Xuan Shen , Rui Xiu , Jingwei Zhang

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.

中文翻译:

高光谱散射图像与集成学习相结合的鸡蛋新鲜度模糊检测

散射高光谱技术是一种无损检测方法,具有许多优点。在此,我们提出一种提高鸡蛋新鲜度准确性的方法,研究光源入射角对鸡蛋新鲜度的影响,并解释其机理。多种弱分类器根据预处理后的光谱对鸡蛋进行分类,并通过特征波长提取来获得三个精度最高的分类器。这三个分类器用作堆叠集成学习的元模型,以将最高准确度从96.25%提高到100%。此外,鸡蛋的散射,反射,透射和混合高光谱的最高准确度分别为100.00%,88.75%,95.00%和96.25%,这表明用于鸡蛋新鲜度检测的散射高光谱要优于其他鸡蛋。此外,精确度与入射角成反比,即入射角越小,相机收集的散射光比例就越大,该散射光包含的卵生化参数比反射和透射的更多。这些结果对于提高无损检测的准确性和选择光源的入射角非常重要,它们对于在线无损检测具有潜在的应用。
更新日期:2020-09-25
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