Application of machine-vision techniques to fish-quality assessment

被引:82
|
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 50 条
  • [41] A machine-vision approach for automated pain measurement at millisecond timescales
    Jones, Jessica M.
    Foster, William
    Twomey, Colin R.
    Burdge, Justin
    Ahmed, Osama M.
    Pereira, Talmo D.
    Wojick, Jessica A.
    Corder, Gregory
    Plotkin, Joshua B.
    Abdus-Saboor, Ishmail
    ELIFE, 2020, 9
  • [42] Machine-Vision Based Defect Detection Algorithm for Packaging Bags
    Li Dan
    Bai Guojun
    Jin Yuanyuan
    Tong Yan
    LASER & OPTOELECTRONICS PROGRESS, 2019, 56 (09)
  • [43] A DISTORTION-CORRECTION SCHEME FOR INDUSTRIAL MACHINE-VISION APPLICATIONS
    BUTLER, DA
    PIERSON, PK
    IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 1991, 7 (04): : 546 - 551
  • [44] Experimental investigation of human and machine-vision arrangements in inspection tasks
    Sylla, C
    CONTROL ENGINEERING PRACTICE, 2002, 10 (03) : 347 - 361
  • [45] Machine-Vision based obstacle avoidance system for robot system
    Tsai, Cheng-Pei
    Chuang, Chin-Tun
    Lu, Ming-Chih
    Wang, Wei-Yen
    Su, Shun-Feng
    Chang, Shyang-Lih
    IEEE INTERNATIONAL CONFERENCE ON SYSTEM SCIENCE AND ENGINEERING (ICSSE 2013), 2013, : 273 - 277
  • [46] POTENTIAL OF MACHINE-VISION LIGHT-MICROSCOPY IN TOXICOLOGIC PATHOLOGY
    TAYLOR, DL
    DEBIASIO, R
    LAROCCA, G
    PANE, D
    POST, P
    KOLEGA, J
    GIULIANO, K
    BURTON, K
    GOUGH, B
    DOW, A
    YU, J
    WAGGONER, AS
    FARKAS, DL
    TOXICOLOGIC PATHOLOGY, 1994, 22 (02) : 145 - 159
  • [47] A machine-vision method for automatic classification of stellar halo substructure
    Hendel, David
    Johnston, Kathryn V.
    Patra, Rohit K.
    Sen, Bodhisattva
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2019, 486 (03) : 3604 - 3616
  • [48] The use of machine vision for assessment of fodder quality
    Dunn, Mark T.
    Billingsley, John
    14TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND MACHINE VISION IN PRACTICE 2007, PROCEEDINGS, 2007, : 179 - +
  • [49] Precision band spraying with machine-vision guidance and adjustable yaw nozzles
    ASAE
    不详
    不详
    Transactions of the American Society of Agricultural Engineers, 1997, 40 (01): : 29 - 36
  • [50] A 3-DIMENSIONAL MACHINE-VISION APPROACH FOR AUTOMATIC ROBOT PROGRAMMING
    TSAI, DM
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1995, 12 (01) : 23 - 48