Application of machine-vision techniques to fish-quality assessment

被引:89
作者
Dowlati, Majid [1 ,2 ]
Mohtasebi, Seyed Saeid [2 ]
de la Guardia, Miguel [1 ]
机构
[1] Univ Valencia, Dept Analyt Chem, E-46100 Burjassot, Spain
[2] Univ Tehran, Fac Agr Engn & Technol, Dept Agr Machinery Engn, Karaj, Iran
关键词
Color analysis; Defect; Fish; Image analysis; Image processing; Inspection; Machine vision; Non-destructive method; Quality assessment; Visible range; SALMON SALMO-SALAR; TROUT ONCORHYNCHUS-MYKISS; COMPUTER VISION; IMAGE-ANALYSIS; RIGOR-MORTIS; PRE-RIGOR; MEASURING COLOR; FOOD-PRODUCTS; FILLETS; WEIGHT;
D O I
10.1016/j.trac.2012.07.011
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Machine vision is a non-destructive, rapid, economic, consistent and objective inspection tool and is also an evaluation technique based on image analysis and processing with a variety of applications. We review the use of machine vision and imaging technologies for fish-quality assessment. This review updates and condenses a representative selection of recent research and industrial solutions proposed in order to evaluate the general trends of machine vision and image processing in the visible range applied for inspection of fish and fish products. In order to determine freshness and composition, it is necessary to measure and to evaluate size and volume, to estimate weight, to measure shape parameters, to analyze skin and fillet in different color shades, to recognize fish species and sex, and to detect defects. Considering the overall trends, we propose some future directions for research. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:168 / 179
页数:12
相关论文
共 85 条
[1]   A review on correlations between fish freshness and pH during cold storage [J].
Abbas, Kassim A. ;
Mohamed, A. ;
Jamilah, B. ;
Ebrahimian, M. .
American Journal of Biochemistry and Biotechnology, 2008, 4 (04) :416-421
[2]  
Alasalvar C., 2010, Handbook of seafood quality, safety and health applications, P1
[3]  
Balaban M. O., 2005, Journal of Aquatic Food Product Technology, V14, P5, DOI 10.1300/J030v14n02_02
[4]   Prediction of the Weight of Alaskan Pollock Using Image Analysis [J].
Balaban, Murat O. ;
Chombeau, Melanie ;
Cirban, Dilsat ;
Gumus, Bahar .
JOURNAL OF FOOD SCIENCE, 2010, 75 (08) :E552-E556
[5]   Using Image Analysis to Predict the Weight of Alaskan Salmon of Different Species [J].
Balaban, Murat O. ;
Sengor, Gulgun F. Unal ;
Gil Soriano, Mario ;
Guillen Ruiz, Elena .
JOURNAL OF FOOD SCIENCE, 2010, 75 (03) :E157-E162
[6]   An automated salmonid slaughter line using machine vision [J].
Bonder, Morten Steen ;
Mathiassen, John Reidar ;
Vebenstad, Petter Aaby ;
Misimi, Ekrem ;
Bar, Eirin Marie Skjondal ;
Toldnes, Bendik ;
Ostvik, Stein Ove .
INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION, 2011, 38 (04) :399-405
[7]  
Botta J., 1995, Evaluation of Seafood Freshness Quality
[8]  
Bremner H. A., 2000, Journal of Aquatic Food Product Technology, V9, P5, DOI 10.1300/J030v09n03_02
[9]   Toward practical definitions of quality for food science [J].
Bremner, HA .
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION, 2000, 40 (01) :83-90
[10]   Inspection and grading of agricultural and food products by computer vision systems - a review [J].
Brosnan, T ;
Sun, DW .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2002, 36 (2-3) :193-213