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首页> 外文期刊>Journal of food engineering >Freshness assessment of gilthead sea bream (Sparus aurata) by machine vision based on gill and eye color changes
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Freshness assessment of gilthead sea bream (Sparus aurata) by machine vision based on gill and eye color changes

机译：基于g和眼睛颜色变化的机器视觉对金头鲷（Sparus aurata）的新鲜度评估

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摘要

The fish freshness was evaluated using machine vision technique through color changes of eyes and gills of farmed and wild gilthead sea bream (Sparus aurata), being employed lightness (L~*), redness (a~*), yellowness (b~*), chroma (c~*), and total color difference (ΔE) parameters during fish ice storage. A digital color imaging system, calibrated to provide accurate CIELAB color measurements, was employed to record the visual characteristics of eyes and gills. The region of interest was automatically selected using a computer program developed in MATLAB software. L~*, b~* and △E of eyes increased with storage time, while c~* decreased. The a' parameter of fish eyes did not show clear a trend with storage time. The L~* b~* and ΔE of fish gills increased with storage time, but a* and c* decreased. Regression analysis and artificial neural networks approaches were used to correlate the eyes and gills color parameters with the time of storage and a strong correlation was found between color parameters and storage day. Gills color changes were more precise than those found for eyes in order to evaluate the fish freshness. However, the gills cover should be removed for taking the images and thus, the method is destructive and time-consuming. Therefore, the color parameters of fish eyes can be used as a green, low cost and easy method for fast and on-line assessing of fish freshness in food industry.
机译：使用机器视觉技术，通过对养殖的和野生的金头鲷（Sparus aurata）的眼睛和g的颜色变化进行评估，以评估鱼的新鲜度，并采用亮度（L〜*），红色（a〜*），黄色（b〜*）鱼冰储存过程中的色度，色度（c〜*）和总色差（ΔE）参数。使用经过校准以提供准确的CIELAB颜色测量值的数字彩色成像系统来记录眼睛和腮的视觉特征。使用在MATLAB软件中开发的计算机程序可以自动选择感兴趣的区域。眼睛的L〜*，b〜*和△E随着保存时间的增加而增加，而c〜*降低。鱼眼的a'参数没有显示出随储存时间的明显趋势。鱼g的L〜* b〜*和ΔE随着贮藏时间的增加而增加，但a *和c *降低。使用回归分析和人工神经网络方法将眼睛和腮的颜色参数与存储时间相关联，并且发现颜色参数与存储日期之间存在很强的相关性。为了评估鱼的新鲜度，的颜色变化比眼睛发现的颜色变化更精确。但是，应取下s盖以拍摄图像，因此该方法具有破坏性且耗时。因此，鱼眼的颜色参数可以作为一种绿色，低成本，简便的方法，用于食品行业中鱼类新鲜度的快速在线评估。

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  • 来源
    《Journal of food engineering》 |2013年第2期|277-287|共11页
  • 作者

    Majid Dowlati; Seyed Saeid Mohtasebi; Mahmoud Omid; Seyed Hadi Razavi; Mansour Jamzad; Miguel de la Guardia;

  • 作者单位

    Agricultural Machinery Engineering Department, Faculty of Agricultural Engineering and Technology. University of Tehran, Karaj, Iran ,Agricultural Machinery Engineering, Department, Faculty of Agriculture, University of Jiroft, Jiroft, Iran;

    Agricultural Machinery Engineering Department, Faculty of Agricultural Engineering and Technology. University of Tehran, Karaj, Iran;

    Agricultural Machinery Engineering Department, Faculty of Agricultural Engineering and Technology. University of Tehran, Karaj, Iran;

    Department of Food Science and Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran;

    Faculty of Computer Engineering Sharif University of Technology, Tehran, Iran;

    Department of Analytical Chemistry, University of Valencia, 46100 Burjassot, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Machine vision; Fish freshness; Fish eye; Fish gill; Color parameters; Ice storage;

    机译：机器视觉鱼的新鲜度;鱼眼;鱼g;颜色参数;冰储存;

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