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Principles, developments and applications of computer vision for external quality inspection of fruits and vegetables: A review

文献类型： 外文期刊

作者： Zhang, Baohua 1 ; Huang, Wenqian 1 ; Li, Jiangbo 1 ; Zhao, Chunjiang 1 ; Fan, Shuxiang 1 ; Wu, Jitao 1 ; Liu, Chenglia 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

2.Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China

关键词： Computer vision;Hyperspectral imaging;Multispectral imaging;External quality inspection;Fruits;Vegetables

期刊名称：FOOD RESEARCH INTERNATIONAL （ 影响因子：6.475； 五年影响因子：6.508 ）

ISSN： 0963-9969

年卷期： 2014 年 62 卷

页码：

收录情况： SCI

摘要： Appearance is a very important sensory quality attribute of fruits and vegetables, which can influence not only their market value, consumer's preferences and choice but also their internal quality to some extent. External quality of fruits and vegetables is generally evaluated by considering their color, texture, size, shape, as well as the visual defects. External quality inspection of fruits and vegetables manually is a time-consuming and labor intensive work Over the past decades, computer vision systems, including traditional computer vision system, hyperspectral computer vision system, and multispectral computer vision system, have been widely used in the food industry, and proved to be scientific and powerful tools for the automatic external quality inspection of food and agricultural products. Many researches based on spatial image and/or spectral image processing and analysis have been published proposing the use of computer vision technique in the field of external quality inspection of fruits and vegetables. This paper presents a detailed overview of the comparative introduction, latest developments and applications of computer vision systems in the external quality inspection of fruits and vegetables. Additionally, the principal components, basic theories, and corresponding processing and analytical methods are also reported in this paper. (C) 2014 Elsevier Ltd. All rights reserved.

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