title: Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances.
abstract: With consumer concerns increasing over food quality and safety, the food industry has begun to pay much more attention to the development of rapid and reliable food-evaluation systems over the years. As a result, there is a great need for manufacturers and retailers to operate effective real-time assessments for food quality and safety during food production and processing. Computer vision, comprising a nondestructive assessment approach, has the aptitude to estimate the characteristics of food products with its advantages of fast speed, ease of use, and minimal sample preparation. Specifically, computer vision systems are feasible for classifying food products into specific grades, detecting defects, and estimating properties such as color, shape, size, surface defects, and contamination. Therefore, in order to track the latest research developments of this technology in the agri-food industry, this review aims to present the fundamentals and instrumentation of computer vision systems with details of applications in quality assessment of agri-food products from 2007 to 2013 and also discuss its future trends in combination with spectroscopy.
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
authors.forename: Ji
authors.initials: J
authors.lastname: Ma
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.|b Food Refrigeration and Computerised Food Technology, Agriculture and Food Science Centre, University College Dublin, National University of Ireland , Belfield , Dublin 4 , Ireland.
authors.forename: Da-Wen
authors.initials: DW
authors.lastname: Sun
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
authors.forename: Jia-Huan
authors.initials: JH
authors.lastname: Qu
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
authors.forename: Dan
authors.initials: D
authors.lastname: Liu
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
authors.forename: Hongbin
authors.initials: H
authors.lastname: Pu
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
authors.forename: Wen-Hong
authors.initials: WH
authors.lastname: Gao
authors.affiliation: a College of Light Industry and Food Sciences, South China University of Technology , Guangzhou , PR China.
authors.forename: Xin-An
authors.initials: XA
authors.lastname: Zeng
mesh_terms: D000383:Agriculture / Q000379:methods / Q000639:trends; D000818:Animals; D005513:Food Inspection / Q000379:methods* / Q000639:trends; D063427:Food Quality; D005525:Food-Processing Industry / Q000379:methods / Q000639:trends; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000639:trends; D008462:Meat-Packing Industry / Q000379:methods / Q000639:trends; D011786:Quality Control
keywords: 3D; Computer vision; agri-food products; applications; hyperspectral imaging; image processing; quality and safety; sonar