DCT-based characterization of milk products using diffuse reflectance images

Sara Sharifzadeh, Jacob L. Skytte, Line H. Clemmensen, Bjarne K. Ersbøll

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

2 Citations (Scopus)

Abstract

We propose to use the two-dimensional Discrete Cosine Transform (DCT) for decomposition of diffuse reflectance images of laser illumination on milk products in different wavelengths. Based on the prior knowledge about the characteristics of the images, the initial feature vectors are formed at each wavelength. The low order DCT coefficients are used to quantify the optical properties. In addition, the entropy information of the higher order DCT coefficients is used to include the illumination interference effects near the incident point. The discrimination powers of the features are computed and used to do wavelength and feature selection. Using the selected features of just one band, we could characterize and discriminate eight different milk products. Comparing this result with the current characterization method based of a fitted log-log linear model, shows that the proposed method can discriminate milk from yogurt products better.
Original languageEnglish
Title of host publication2013 18th International Conference on Digital Signal Processing (DSP)
PublisherIEEE
Number of pages6
ISBN (Print)978-1-4673-5807-1
DOIs
Publication statusPublished - 1 Jul 2013
Externally publishedYes
Event18th International Conference on Digital Signal Processing (DSP) - Fira, Greece
Duration: 1 Jul 20133 Jul 2013
Conference number: 18

Conference

Conference18th International Conference on Digital Signal Processing (DSP)
CountryGreece
CityFira
Period1/07/133/07/13

Keywords

  • Reflectivity
  • Dairy products
  • Optical reflection
  • Optical imaging

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  • Cite this

    Sharifzadeh, S., Skytte, J. L., Clemmensen, L. H., & Ersbøll, B. K. (2013). DCT-based characterization of milk products using diffuse reflectance images. In 2013 18th International Conference on Digital Signal Processing (DSP) IEEE. https://doi.org/10.1109/ICDSP.2013.6622669