Abstract
High speed data processing for online food quality inspection using hyperspectral imaging (HSI) is challenging as over hundred spectral images have to be analyzed simultaneously. In this study, a real-time pixel based early apple bruise detection system based on HSI in the shortwave infrared (SWIR) range has been developed. This systems consists of a novel, homogeneous SWIR illumination unit and a line scan camera. The system performance was tested on Jonagold apples bruised less than two hours before scanning. Partial least squares-discriminant analysis was used to discriminate bruised pixel spectra from sound pixel spectra. As the glossiness of many fruit and vegetables limits the accuracy in the detection of defects, several reflectance calibrations and pre-processing techniques were compared for glare correction and maximizing the signal to noise ratio. With the best combination of first derivative and mean centering, followed by image post-processing, this system was able to detect fresh bruises in thirty apples with 98% accuracy at the pixel level with a processing time per apple below 200 ms.
Original language | English (US) |
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Pages (from-to) | 215-226 |
Number of pages | 12 |
Journal | Food Control |
Volume | 66 |
DOIs | |
State | Published - Aug 1 2016 |
Keywords
- Food sorting
- Glare correction
- Hyperspectral imaging
- Pixel-based classification
- Real-time
- SWIR
- Short wave infrared
- Uniform illumination
ASJC Scopus subject areas
- Biotechnology
- Food Science