高光谱成像
不可用
遥感
成像光谱仪
计算机科学
人工智能
计算机视觉
工程类
可靠性工程
地理
分光计
量子力学
物理
作者
Mohammed Kamruzzaman,Dongxu Sun
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2016-01-01
卷期号:: 111-139
被引量:31
标识
DOI:10.1016/b978-0-12-802232-0.00005-0
摘要
Traditional methods are still widely used in most food industries due to the unavailability of smart alternatives. Traditional destructive methods are not suitable in today's hypercompetitive marketplace. Consequently, a cost-effective, efficient, rapid, and reliable method is required. In particular, there is a great interest in developing nondestructive optical technologies that have the capability of monitoring in a real-time assessment. Among them, hyperspectral imaging techniques have received ample attention. Hyperspectral imaging systems provide spatial and spectral details; therefore, these systems introduce new sensing facilities that enable improved inspection. Moreover, hyperspectral imaging can be used for online monitoring if properly optimized. This chapter first describes the fundamentals of hyperspectral imaging techniques, followed by an overview of multivariate data analysis, optimal wavelength selection, model evaluation, multivariate image analysis, and software for data/image analysis. Finally, the applications of hyperspectral imaging for evaluating quality, safety, and authenticity of muscle foods are illustrated.
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