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Journal of Food Measurement and Characterization

, Volume 8, Issue 3, pp 180–194 | Cite as

Complex assessment of grain quality using image and spectra analyses

  • Mirolyub I. Mladenov
  • Martin P. DejanovEmail author
  • Roumiana Tsenkova
Original Paper
  • 195 Downloads

Abstract

The paper presents methods and tools for assessment of main quality features of grain samples based on color image and spectra analyses. Visible features like color, shape, and dimensions of the grain sample elements are extracted from the images. Information about its color and surface texture is obtained from the grain spectral characteristics. The categorization of the grain sample elements in three quality groups is accomplished using two data fusion approaches. The first approach fuses the results from color and shape characteristics obtained using image analysis only. The second approach fuses the shape data obtained by image analysis and the color and surface texture data obtained by spectra analysis. The three data fusion methods give the following errors in the categorization of the grain sample elements: 15.3, 8.6, 5.3 %.

Keywords

Grain sample quality assessment Color image analysis Spectra analysis Classification Data fusion 

Notes

Acknowledgments

This investigation is a part of implementation of the research project “Intelligent Technologies for Assessment of Quality and Safety of Food Agricultural Products”, funded by the Bulgarian National Science Fund.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Mirolyub I. Mladenov
    • 1
  • Martin P. Dejanov
    • 1
    Email author
  • Roumiana Tsenkova
    • 2
  1. 1.Department of Automatics and MechatronicsUniversity of RousseRuseBulgaria
  2. 2.Biomeasurement Technology LaboratoryKobe UniversityKobeJapan

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