Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances

被引:72
作者
Ma, Ji [1 ]
Sun, Da-Wen [1 ,2 ]
Qu, Jia-Huan [1 ]
Liu, Dan [1 ]
Pu, Hongbin [1 ]
Gao, Wen-Hong [1 ]
Zeng, Xin-An [1 ]
机构
[1] S China Univ Technol, Coll Light Ind & Food Sci, Guangzhou, Guangdong, Peoples R China
[2] Natl Univ Ireland Univ Coll Dublin, Agr & Food Sci Ctr, Food Refrigerat & Computerised Food Technol, Dublin 4, Ireland
基金
中国博士后科学基金;
关键词
Computer vision; image processing; quality and safety; applications; agri-food products; hyperspectral imaging; 3D; sonar; INTRAMUSCULAR FAT-CONTENT; MACHINE VISION; IMAGE-ANALYSIS; MOISTURE TRANSFER; MUSA-CAVENDISH; THICKNESS MEASUREMENT; ISOTHERM EQUATIONS; COLOR INFORMATION; BROWNING KINETICS; TEXTURE FEATURES;
D O I
10.1080/10408398.2013.873885
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
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.
引用
收藏
页码:113 / 127
页数:15
相关论文
共 148 条
[51]   Recent advances in the use of computer vision technology in the quality assessment of fresh meats [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul .
TRENDS IN FOOD SCIENCE & TECHNOLOGY, 2011, 22 (04) :185-197
[52]   Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul ;
Valous, Nektarios A. ;
Mendoza, Fernando ;
Ward, Paddy .
MEAT SCIENCE, 2010, 84 (04) :711-717
[53]   Correlation of consumer assessment of longissimus dorsi beef palatability with image colour, marbling and surface texture features [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul ;
Brandon, Karen ;
White, Anna-Marie .
MEAT SCIENCE, 2010, 84 (03) :564-568
[54]   Prediction of beef palatability from colour, marbling and surface texture features of longissimus dorsi [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul .
JOURNAL OF FOOD ENGINEERING, 2010, 96 (01) :151-165
[55]   Prediction of beef eating qualities from colour, marbling and wavelet surface texture features using homogenous carcass treatment [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Du, Cheng-Jin ;
Allen, Paul .
PATTERN RECOGNITION, 2009, 42 (05) :751-763
[56]   Automatic segmentation of beef longissimus dorsi muscle and marbling by an adaptable algorithm [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul .
MEAT SCIENCE, 2009, 83 (02) :187-194
[57]   Comparison of various wavelet texture features to predict beef palatability [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul .
MEAT SCIENCE, 2009, 83 (01) :82-87
[58]   Comparison of the predictive power of beef surface wavelet texture features at high and low magnification [J].
Jackman, Patrick ;
Sun, Da-Wen ;
Allen, Paul .
MEAT SCIENCE, 2009, 82 (03) :353-356
[59]   An experimental machine vision system for sorting sweet tamarind [J].
Jarimopas, Bundit ;
Jaisin, Nitipong .
JOURNAL OF FOOD ENGINEERING, 2008, 89 (03) :291-297
[60]   Inspection of the distribution and amount of ingredients in pasteurized cheese by computer vision [J].
Jeliñski, Tomasz ;
Du, Cheng-Jin ;
Sun, Da-Wen ;
Fornal, Jozef .
JOURNAL OF FOOD ENGINEERING, 2007, 83 (01) :3-9