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Image Processing Methods and Fractal Analysis for Quantitative Evaluation of Size, Shape, Structure and Microstructure in Food Materials

  • Conference paper

Part of the book series: Food Engineering series ((FSES))

In recent years, image analysis methods have been applied for quantitative evaluation of morphology, structure and microstructure of foodstuffs. Image processing techniques usually consist of five steps (Castleman, 1996; Pedreschi et al., 2004; Du and Sun, 2004), which are: 1) image capture, 2) pre-processing, 3) image segmentation, 4) feature extraction and 5) classification. In food engineering applications, some or all of these steps have been used to extract information from food images captured with different acquisition systems. The extracted information is useful to translate the food system complexity to numeric data that shall be analyzed to improve the understanding of structure-function relationships of complex systems, such as food and biological materials. On the other hand, fractal analysis has been successfully applied for quantitative evaluation of irregular surfaces and textures of biological materials (Quevedo et al. 2002; Chanona et al., 2003; Villalobos et. al, 2005), and also to characterize ruggedness and geometric complexities of different food particles, such as instant coffee, skim milk, potato starch powder, maltodextrin particles and others (Peleg and Normand, 1985; Barletta and Barbosa, 1993; Shafiur, 1997; Alamilla et al., 2005). The key to quantifying the irregularity of the contours and surfaces in food materials is to evaluate the apparent fractal dimension (FD) by extracting it from the images of structural and microstructural features. Results from fractal analysis are important in examining the architecture and structure-functionality properties of food products.

The objective of this contribution was to provide a brief description of diverse methods for image processing and fractal analysis of acquired data in our laboratory for quantitative evaluation of size, shape, structure and microstructure in different biological/food materials.

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References

  • Alamilla, B.L, Chanona, P.J.J., Jiménez, A.A.R., and Gutiérrez L.G.F., 2005. Desciption Of Morphological Changes Of Particles Along Spray Drying, J. Food Eng. 67:179–184.

    Article  Google Scholar 

  • Barletta, B.J., and Barbosa C.G.V., 1993, Fractal Analysis to Characterize Ruggedness Changes in Tapped Agglomerated Food Powders, J. Food Sci. 58(5):1030–1035, 1046.

    Article  Google Scholar 

  • Castleman K.R., 1996, Digital Image Processing. Prentice Hall, Englewood Cliffs, pp. 667.

    Google Scholar 

  • Chakraborti, R.K., Gardner, K.H., Atkinson J.F., and Van Benschoten J.E., 2003, Changes in Fractal Dimension During Aggregation, Water Res. 37:873–883.

    Article  CAS  Google Scholar 

  • Chanona, P.J.J, Alamilla, B.L., Farrera, R.R.R., Quevedo, R, Aguilera, J.M., and Gutiérrez L.G.F., 2003, Description of the Convective Air Drying of a Food Model by Means of the Fractal Theory, Food Sci. Technol. Int. 9(3):207–213.

    Article  Google Scholar 

  • Crowley, P. Grau, H., and Arendt E.K., 2000, Influence of Additives and Mixing Time on Crumb Grain Characteristics of Wheat Bread, Cereal Chem. 77(3):370–375.

    Article  CAS  Google Scholar 

  • Du, C., and Sun D., 2004, Recent Developments in the Applications of Image Processing Techniques for Food Quality Evaluation, Trends Food Sci. Technol. 15:230–249.

    Article  CAS  Google Scholar 

  • Gonzalez-Barron, U., and Butler F., 2006, A Comparison of Seven Thresholding Techniques with the K-Means Clustering Algorithm for Measurement of Bread-Crumb Features by Digital Image Analysis, J. Food Eng. 74:268–278.

    Article  Google Scholar 

  • Handen P., 2006, Scanning Differential Box counting (SDBC) codec, version 1.0. Plug-in of ImageJ. (June 2006);http://rsb.info.nhi.gov/ij/.

  • Idarraga, G., Ramos, J., Zuñiga, V., Sahin, T., and Young R.A., 1999, Pulp and Paper from Blue Agave Waste From Tequila Production, J. Agric. Food Chem. 47:4450–4455.

    Article  CAS  Google Scholar 

  • Kenkel, N.C., and Walker D.J., 1996, Fractals in the Biological Sciences. [On-line] (June 1, 2006):http://www.umanitoba.ca/faculties/science/botany/labs/ecology/fractals/fractal.html.

  • Olsen, E R, Ramsey, R.D., and Winn D.S., 1993, A Modified Fractal Dimension as a Measure of Landscape Diversity, Photogramm. Eng. Rem. S. 59:1517–1520.

    Google Scholar 

  • Pedreschi, F., Mery, D., Mendoza, F., and Aguilera, J.M., 2004, Classification of Potato Chips Using Pattern Recognition, J. Food Sci. 69:E1–E7.

    Google Scholar 

  • Peleg, M., and Normand M.D., 1985, Characterization of the Ruggedness of Instant Coffee Particles by Natural Fractals, J. Food Sci. 50(3):829–831.

    Article  Google Scholar 

  • Quevedo, R., López, G.R., Aguilera, J.M., and Cadoche L., 2002, Description of Food Surfaces and Microstructural Changes Using Fractal Image Texture Analysis, J. Food Eng. 53:361–371.

    Article  Google Scholar 

  • Riva, M., and Fessas D., 1999, New Physical Approach to Sliced Toasted Bread Characterization, Ind. Aliment.-Italy 38(381):521–526.

    Google Scholar 

  • Riva, M., and Liviero S., 2000, Image Analysis Approach to Characterize the Bread Cooking Kinetic, Ind. Aliment.-Italy 39(395):593–660.

    Google Scholar 

  • Sapirstein, H.D., Roller, R., and Bushuk W., 1994, Instrumental Measurement of Bread Crumb Grain by Digital Image Analysis, Cereal Chem. 71(4):383–391.

    Google Scholar 

  • Scanlon, M.G., and Zghal M.C., 2001, Bread Properties and Crumb Structure, Food Res. Int. 34:841–864.

    Article  Google Scholar 

  • Scher, J., and Hardy J., 2002, A New Approach of Sensorial Evaluation of Cooked Cereal Foods: Fractal Analysis of Reological Data, EPJ Applied Physic, 20(2):159–163.

    Article  Google Scholar 

  • Scher, J., Berton, B., and Hardy J., 2004, Mechanical and Sensory Characterization of Died Bread-Crumbs: Application of Fractal Concept, Sci. Aliment. 24(4):279–287.

    Article  Google Scholar 

  • Shafiur R.M., 1997, Physical Meaning and Interpretation of Fractal Dimensions of Fine Particles Measured by Different Methods, J. Food Eng. 32:447–456.

    Article  Google Scholar 

  • Villalobos, R. Chanona, J., Hernández, P., Gutiérrez, G., and Chiralt A., 2005, Gloss and Transparency of Hidroxypropyl Methylcellulose Films Containing Surfactants as Affected by Their Microstructure, Food Hydrocollid. 19:53–61.

    Article  CAS  Google Scholar 

  • Zghal, M.C., Scanlon, M.G., and Sapirstein H.D., 2001, Effects of Flour Strength, Baking Absorption, and Processing Conditions on the Structure and Mechanical Properties of Bread Crumb, Cereal Chem. 78(1):1–7.

    Article  CAS  Google Scholar 

  • Zghal, M.C., Scanlon, M. G., and Sapirstein H.D., 1999, Prediction of Bread Crumb Density by Digital Image Analysis, Cereal Chem. 75(5):734–742.

    Article  Google Scholar 

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Chanona-Pérez, J. et al. (2008). Image Processing Methods and Fractal Analysis for Quantitative Evaluation of Size, Shape, Structure and Microstructure in Food Materials. In: Gutiérrez-López, G.F., Barbosa-Cánovas, G.V., Welti-Chanes, J., Parada-Arias, E. (eds) Food Engineering: Integrated Approaches. Food Engineering series. Springer, New York, NY. https://doi.org/10.1007/978-0-387-75430-7_16

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