论文标题
使用传播多光谱成像对掺假和重复使用椰子油的定量评估
Quantitative Assessment of Adulteration and Reuse of Coconut Oil Using Transmittance Multispectral Imaging
论文作者
论文摘要
椰子油以其广泛的用途而闻名，通常与其他可食用的油融合在一起。在食物制备中反复使用椰子油可能导致许多健康问题。可用于评估石油质量的现有方法是费力且耗时的。因此，我们提出了一个基于成像系统的硬件和基于图像加工的算法，以估计椰子油与棕榈油作为掺假剂的掺假。在训练样本中，掺假水平和bhattacharyya距离之间的掺假水平和bhattacharyya距离之间存在明显的功能关系。此后，提出了另一种算法来开发基于光谱簇的分类器，以确定椰子油的再加热和再利用的效果。对于不同水平的再加热油类别，获得了不同的簇，并且在训练样品上进行了0.983进行分类。此外，使用内部开发的基于透射的多光谱成像系统生成了所提出算法的输入图像。
Coconut oil known for its wide range of uses is often adulterated with other edible oils. Repeated use of coconut oil in food preparation could lead to many health issues. Existing methods available for evaluating quality of oil are laborious and time consuming. Therefore, we propose an imaging system hardware and image processing-based algorithm to estimate the adulteration of coconut oil with palm oil as the adulterant. A clear functional relationship between adulteration level and Bhattacharyya distance was observed as R2 = 0.9876 on the training samples. Thereafter, another algorithm is proposed to develop a spectral-clustering based classifier to determine the effect of reheat and reuse of coconut oil. Distinct clusters were obtained for different levels of reheated oil classes and the classification was performed with an accuracy of 0.983 on training samples. Further, the input images for the proposed algorithms were generated using an in-house developed transmittance based multispectral imaging system.
