Application of machine-vision techniques to fish-quality assessment

被引：87
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
来源：
TRAC-TRENDS IN ANALYTICAL CHEMISTRY | 2012年 / 40卷
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
  • [11] Improving quality inspection of food products by computer vision - a review
    Brosnan, T
    Sun, DW
    [J]. JOURNAL OF FOOD ENGINEERING, 2004, 61 (01) : 3 - 16
  • [12] Machine vision technology for agricultural applications
    Chen, YR
    Chao, KL
    Kim, MS
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2002, 36 (2-3) : 173 - 191
  • [13] Connell J.J., 1995, Control of Fish Quality, V4th
  • [14] An innovative machine for automated cutting of fish
    deSilva, CW
    Wickramarachchi, N
    [J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS, 1997, 2 (02) : 86 - 98
  • [15] Computer vision and robotics techniques in fish farms
    Dios, JRMD
    Serna, C
    Ellero, A
    [J]. ROBOTICA, 2003, 21 : 233 - 243
  • [16] Recent developments in the applications of image processing techniques for food quality evaluation
    Du, CJ
    Sun, DW
    [J]. TRENDS IN FOOD SCIENCE & TECHNOLOGY, 2004, 15 (05) : 230 - 249
  • [17] Measurement of sole activity by digital image analysis
    Duarte, S.
    Reig, L.
    Oca, J.
    [J]. AQUACULTURAL ENGINEERING, 2009, 41 (01) : 22 - 27
  • [18] Atlantic salmon skin and fillet color changes effected by perimortem handling stress, rigor mortis, and ice storage
    Erikson, U.
    Misimi, E.
    [J]. JOURNAL OF FOOD SCIENCE, 2008, 73 (02) : C50 - C59
  • [19] Bleeding of anaesthetized and exhausted Atlantic salmon: body cavity inspection and residual blood in pre-rigor and smoked fillets as determined by various analytical methods
    Erikson, Ulf
    Misimi, Ekrem
    Fismen, Britta
    [J]. AQUACULTURE RESEARCH, 2010, 41 (04) : 496 - 510
  • [20] Length-weight relationships of five fish species in Epe lagoon, Nigeria
    Fafioye, OO
    Oluajo, OA
    [J]. AFRICAN JOURNAL OF BIOTECHNOLOGY, 2005, 4 (07): : 749 - 751
123456789