Statistical Quality Assessment of Pre-fried Carrots Using Multispectral Imaging

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Multispectral imaging is increasingly being used for quality assessment of food items due to its non-invasive benefits. In this paper, we investigate the use of multispectral images of pre-fried carrots, to detect changes over a period of 14 days. The idea is to distinguish changes in quality from spectral images of visible and NIR bands. High dimensional feature vectors were formed from all possible ratios of spectral bands in 9 different percentiles per piece of carrot. We propose to use a multiple hypothesis testing technique based on the Benjamini-Hachberg (BH) method to distinguish possible significant changes in features during the inspection days. Discrimination by the SVM classifier supported these results. Additionally, 2-sided t-tests on the predictions of the elastic-net regressions were carried out to compare our results with previous studies on fried carrots. The experimental results showed that the most significant changes occured in day 2 and day 14.
Original languageEnglish
Title of host publicationImage Analysis : 18th Scandinavian Conference, SCIA 2013, Espoo, Finland, June 17-20, 2013. Proceedings
Publication date2013
ISBN (Print)978-3-642-38885-9
ISBN (Electronic)978-3-642-38886-6
Publication statusPublished - 2013
Event18th Scandinavian Conference on Image Analysis (SCIA 2013) - Espoo, Finland
Duration: 17 Jun 201320 Jun 2013


Conference18th Scandinavian Conference on Image Analysis (SCIA 2013)
Internet address
SeriesLecture Notes in Computer Science


  • Multispectral imaging
  • Multiple hypothesis testing
  • Segmentation
  • Food quality assessment
  • SVM classification
  • Elastic-net regression


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