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  1. 19 de nov. de 2022 · In this research, an automatic algorithm of bread quality assessment using image processing techniques, is proposed. First, color images of bread with different qualities are...

  2. This paper analyze the bread slice images in order to quantify the differences in crumb color of bread products made with different substitution percentages of grape seed flour. Comparative analysis of the results achieved with ImageJ algorithms showed a significant difference between the studied parameters.

    • Liviu Gaceu
    • 2019
  3. 1 de sept. de 2021 · Bread structure analysis was carried out using ImageJ software following the methodology described by Morreale, Garzón, and Rosell (2018). Bread porosity (%), calculated as total cell area and total slice area ratio in percentage, and mean and median cavities or cells area (mm 2 ) were determined.

    • Andrea Aleixandre, Yaiza Benavent-Gil, Elena Velickova, Cristina M. Rosell
    • 2021
  4. 20 de ene. de 2011 · Images were saved as bitmap files, and sRGB colour. Images were cropped at a field of view (FOV) of 4 × 4 cm that represents approximately 36.5% of crumb bread area; then, images were changed to greyscale (8 bit) using the ImageJ software (National Institutes Health, Bethesda, Md, USA).

    • Reynold R. Farrera-Rebollo, Ma. de la Paz Salgado-Cruz, Jorge Chanona-Pérez, Gustavo F. Gutiérrez-Ló...
    • 2012
  5. 1 de mar. de 2015 · This study seeks to compare image analysis techniques (binarization using Otsu’s method and the default ImageJ algorithm, a variation of the iterative intermeans method) for quantification of...

  6. 6 de jun. de 2022 · In this research, an automatic algorithm of bread quality assessment using image processing techniques, is proposed. First, color images of bread with different qualities are photographed and a database of 1250 bread images is prepared.

  7. bread by digital image analysis [12]. The breads were sliced and photographed by a CCD camera in the presence of light inclined to the cutting surface. The brightness scale was calibrated using a gray color card. Then, the slices were separated from the image background and their shape and dimensions were measured.