4.7 Article

Improved algorithm for estimating the optical properties of food products using spatially-resolved diffuse reflectance

期刊

JOURNAL OF FOOD ENGINEERING
卷 212, 期 -, 页码 1-11

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jfoodeng.2017.05.005

关键词

Optical properties; Spatially-resolved; Inverse algorithm; Step-by-step method; Turbid food tissue

资金

  1. China's Scholarship Council (CSC)

向作者/读者索取更多资源

Understanding the optical properties of food products is essential to apply optical methods for quality detection. In this research, the inverse algorithm for estimating the optical properties of food products from spatially-resolved diffuse reflectance was optimized based on the reflectance profiles generated by Monte Carlo simulations. First, the start and end points, namely, the spatial region, of reflectance profiles for parameter estimation were optimized with the unit of mean free path (mfp'). Based on this optimal spatial region with recommended start and end points, an improved step-by-step method was proposed over conventional 1-step (C-1-step) method that used fixed start and end points. Furthermore, the C-1-step method was also modified by using the optimized end point of 16 mfp's and designated as M-1-step method. Results showed that the optimal start point decreased from 3 mfp's to 1.6 mfp's with the increase of mu(s)'/mu(a) value from 10 to 60, while the recommended end point was kept at 16 mfp's. Absolute values of relative errors for the best estimates of mu(a) and mu(s)' using C-1-step and step-by-step methods were 8.7%, 5.6% and 3.5%, 23%, respectively, for a spatial resolution of 0.1 mm. The M-1-step method, with the spatial resolution of 0.1 mm, reduced the estimation errors to 3.8% and 3.7% for mu(a) and mu(s)', representing 56% and 34% improvements over the C-1-step method. Based on the results of M-1-step method, the step-by-step method could also improve estimation accuracy. At last, the effectiveness of the proposed algorithm was validated with real mango samples. The mean absolute percentage errors for estimating mu(a) and mu(s)' by a hyperspectral imaging system combined with the step-by-step method were 9.2% and 5.7%, respectively. (C) 2017 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据