Singular spectrum analysis for hyperspectral imaging based beef eating quality evaluation: a new pre-processing method

Tong Qiao, Jinchang Ren, Jaime Zabalza, Cameron Craigie, Charlotte Maltin, Stephen Marshall

Research output: Contribution to conferencePoster

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Abstract

Hyperspectral imaging (HSI) is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. In recent years, HSI has rapidly matured into one of the most powerful tools for food quality analysis and control. In the project, HSI has been applied for beef eating quality evaluation. Pre-processing of HSI spectral profiles is needed, in order to eliminate undesired noises. Singular spectrum analysis (SSA) will be demonstrated to be an effective pre-processing step in de-noising HSI spectra.
Original languageEnglish
Pages148
Number of pages1
Publication statusPublished - Sep 2014
EventFarm Animal IMaging (FAIM) - Copenhagen, Denmark
Duration: 25 Sep 201426 Sep 2014

Conference

ConferenceFarm Animal IMaging (FAIM)
CountryDenmark
CityCopenhagen
Period25/09/1426/09/14

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Keywords

  • hyperspectral imaging
  • singular spectrum analysis
  • beef quality prediction

Cite this

Qiao, T., Ren, J., Zabalza, J., Craigie, C., Maltin, C., & Marshall, S. (2014). Singular spectrum analysis for hyperspectral imaging based beef eating quality evaluation: a new pre-processing method. 148. Poster session presented at Farm Animal IMaging (FAIM), Copenhagen, Denmark.