Mathematical Morphology on MRI for the Determination of Iberian Ham Fat Content

  • Andrés Caro
  • Marisa Durán
  • Pablo G. Rodríguez
  • Teresa Antequera
  • Ramón Palacios
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)


Intermuscular Fat Content and its distribution during the ripening process of the Iberian ham is a relevant task from the point of view of technological interest. This paper attempts to study the Iberian ham during the ripening process with images obtained from a MRI (Magnetic Resonance Imaging) device using Pattern Recognition and Image Analysis algorithms, in particular Mathematical Morphology techniques. The main advantage of this method is the non-destructive nature. A concrete algorithm is proposed, which is based on the Watershed transformation. In addition, the results are compared with the Otsu thresholding algorithm. The decreases of the total volume in the ripening process are shown. Also the decrease of the meat percentage and intermuscular fat content are calculated. As a conclusion, the viability of these techniques is proved for the possible future utilization in the meat industries to discover new characteristics in the ripening process.


  1. 1.
    Antequera, T., López-Bote, C.J., Córdoba, J.J., García, C., Asensio, M.A., Ventanas, J., Díaz, Y.: Lipid oxidative changes in the processing of Iberian pig hams. Fod. Chem. 54, 105 (1992)CrossRefGoogle Scholar
  2. 2.
    Cava, R., Ventanas, J.: Dinámica y control del proceso de secado del jamón ibérico en condiciones naturales y cámaras climatizadas. In: Prensa, M. (ed.) Tecnología del jamón ibérico, pp. 260–274 (2001)Google Scholar
  3. 3.
    Cernadas, E., Durán, M.L., Antequera, T.: Recognizing Marbling in Dry-Cured Iberian Ham by Multiscale Analysis. Pattern Recognition Letters 23, 1311–1321 (2002)zbMATHCrossRefGoogle Scholar
  4. 4.
    Durán, M.L., Cernadas, E., Caro, A., Antequera, T.: Clasificación de distintos tipos de jamón ibérico utilizando Análisis de Texturas. Revista Elec. Visión por Comp. (5) (2001)Google Scholar
  5. 5.
    Durán, M.L., Caro, A., Cernadas, E., Plaza, A., Petrón, M.J.: A fuzzy schema to evaluate fat content in iberian pig meat images. In: Ibero-American Symp. Patt. Recog., pp. 207–216 (2000)Google Scholar
  6. 6.
    Cernadas, E., Durán, M.L., Rodríguez, P.G., Caro, A., Muriel, E., Palacios, R.: Estimating intramuscular fat content of cured Iberian loin using statistical analysis of its magnetic resonance images. In: 12th Portuguese Conference on Pattern Recognition (2002)Google Scholar
  7. 7.
    Cernadas, E., Plaza, A., Rodríguez, P.G., Durán, M.L., Hernández, J., Antequera, T., Gallardo, R., Villa, D.: Estimation of Dry-Cured Iberian Ham Quality Using Magnetic Resonance Imaging. In: 5th Int. Conf. Applic. Mag. Resonance in Food Science, pp. 46–47 (2000)Google Scholar
  8. 8.
    Cernadas, E., Antequera, T., Rodríguez, P.G., Durán, M.L., Gallardo, R., Villa, D.: Magnetic Resonance Imaging to Classify Loin from Iberian Pigs. In: Mag. Resonance in Food Science. The Royal Society of Chemistry, pp. 239–254 (2001)Google Scholar
  9. 9.
    Antequera, T., Muriel, E., Rodríguez, P.G., Cernadas, E., Ruiz, J.: Magnetic Resonance Imaging as a Predictive Tool for Sensoring Characteristic and Intramuscular Fat Content of Dry-Cured Loin. Int. Journal of Science and Food and Agric. 83, 268–274 (2003)CrossRefGoogle Scholar
  10. 10.
    Caro, A., Rodríguez, P.G., Cernadas, E., Antequera, T.: Disminución volumétrica del jamón ibérico durante su maduración analizando imágenes de Resonancia Magnética mediante Contornos Activos. Revista “Información Tecnológica” 13(3), 175–180 (2002)Google Scholar
  11. 11.
    Beucher, S., Meyer, F.: The Morphological Approach to Segmentation: The Watershed Transformation. In: Dougherty, E.R. (ed.) Math. Morphology in Image Processing, pp. 433–482. Marchel Dekker, New York (1993)Google Scholar
  12. 12.
    Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, New York (1982)zbMATHGoogle Scholar
  13. 13.
    Caro, A., Rodríguez, P.G., Ávila, M., Rodríguez, F., Rodríguez, F.J.: Active Contours Using Watershed Segmentation. In: 9th Int. Workshop on Systems, Signal and Image Processing, Manchester (UK), November 7-8, pp. 340–345 (2002)Google Scholar
  14. 14.
    Otsu, N.: A Threshold Selection Method from Gray-Level Histograms. IEEE Trans. Systems, Man, and Cybernetics SMC-9(1) (January 1979)Google Scholar
  15. 15.
    Durán, M.L., Cernadas, E., Plaza, A., Sánchez, J.M., Rodríguez, F., Petrón, M.J.: Could Machine Vision Replace Chemical Procedure to Evaluate Fat Content in Iberian Pig Meat? An Experimental Study. In: 3rd Int. Conf. on Computer Vision, Pattern Recognition, and Image Processing, Atlantic City, New Jersey (USA), pp. 256–259 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Andrés Caro
    • 1
  • Marisa Durán
    • 1
  • Pablo G. Rodríguez
    • 1
  • Teresa Antequera
    • 2
  • Ramón Palacios
    • 3
  1. 1.Dpto. Informática, Escuela PolitécnicaUniv. ExtremaduraCáceres
  2. 2.Tecnología de los Alimentos, Facultad de VeterinariaUniv. ExtremaduraCáceres
  3. 3.Servicio de RadiodiagnósticoHospital Universitario Infanta CristinaBadajoz

Personalised recommendations