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IMAGE PROCESSING AND HYPERSPECTRAL IMAGING FOR QUALITY CONTROL IN THE POTATO INDUSTRY

Image Processing

The overall objective of this project was the design and analysis of image processing and hyperspectral imaging techniques to automate certain tasks related to quality control in the potato industry which are developed manually until now. The study covered the classical stages of computer vision, but now applied to hyperspectral images: design and implementation of an image acquisition system, preprocessing and segmentation through various image processing techniques, feature extraction, and classification.

Some of the tasks that have been developed are:

  • Classification of tubers depending on their external defects (greening, rotten, etc.).
  • Detecting hollow heart in potatoes using hyperspectral imaging.
  • Estimating area affected by common scab in potatoes using hyperspectral imaging.

We provide to the research community the database (.rar-file 1.52 GiB, md5-checksum, and Readme-file) of a set of hyperspectral images which we used to detect the hollow heart and other deseases in potatoes using hyperspectral information in the infrared spectrum (900 nm to 1700 nm).



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