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. 2023 Aug 20:50:109503.
doi: 10.1016/j.dib.2023.109503. eCollection 2023 Oct.

Images dataset of beef meat samples with different shelf life

Affiliations

Images dataset of beef meat samples with different shelf life

Julieta Domínguez-Soberanes et al. Data Brief. .

Abstract

Three different cuts of meat samples: inside skirt, knuckles, and sirloin were picture captioned on the first and fifth day after purchase. From each type of meat cut, ten pictures were taken at the beginning and the end of the studied shelf life, obtaining 60 different images. The images were taken under control variables in a black acrylic cabin. In addition to the original images, we proportionate another set of 60 processed images. The latter were obtained after color calibration and meat segmentation. All these images could be used for future experiments where the color in meat should be analyzed.

Keywords: Beef meat color; Beef meat images; Inside skirt images; Knuckle images; Sirloin images.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. However, it is essential to mention that the cabin described in the methodology has started a registration process as a utility model.

Figures

Fig 1
Fig. 1
shows examples of the originally captured images. They include the sample code (up-right) and the color checker matrix that can be used for color calibration. The sample letter in the sample code corresponds to the cut: inside skirt (A), knuckles (B), and sirloin (S). The first row corresponds to the first day and the second one to the fifth day after purchase.
Fig 2
Fig. 2
Beef meat samples after color calibration and meat segmentation. The first row corresponds to the first day and the second one to the fifth day after purchase. Columns, from left to right, represent samples of inside skirt, knuckle, and sirloin, respectively.
Fig 3
Fig. 3
Example of the image segmentation. a) Original image. b) Image after pixel classification with SVM. c) Bigger connected component. d) Final image after binary fill holes. Image taken from .

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