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Image Analysis of Foods
Author(s) -
Russ John C.
Publication year - 2015
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/1750-3841.12987
Subject(s) - artificial intelligence , mouthfeel , sorting , image processing , computer vision , confocal , computer science , object (grammar) , biological system , image (mathematics) , chemistry , biology , optics , physics , raw material , programming language , organic chemistry
The structure of foods, both natural and processed ones, is controlled by many variables ranging from biology to chemistry and mechanical forces. The structure also controls many of the properties of the food, including consumer acceptance, taste, mouthfeel, appearance, and so on, and nutrition. Imaging provides an important tool for measuring the structure of foods. This includes 2‐dimensional (2D) images of surfaces and sections, for example, viewed in a microscope, as well as 3‐dimensional (3D) images of internal structure as may be produced by confocal microscopy, or computed tomography and magnetic resonance imaging. The use of images also guides robotics for harvesting and sorting. Processing of images may be needed to calibrate colors, reduce noise, enhance detail, and delineate structure and dimensions. Measurement of structural information such as volume fraction and internal surface areas, as well as the analysis of object size, location, and shape in both 2‐ and 3‐dimensional images is illustrated and described, with primary references and examples from a wide range of applications.