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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Identification of insect damaged wheat kernels using transmittance images

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      Author
      Çataltepe, Z.
      Çetin, A. Enis
      Pearson, T.
      Date
      2004
      Source Title
      Proceedings of the International Conference on Image Processing, IEEE 2004
      Print ISSN
      1522-4880
      Publisher
      IEEE
      Volume
      2
      Pages
      2917 - 2920
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      We used transmittance images and different learning algorithms to classify insect damaged and un-damaged wheat kernels. Using the histogram of the pixels of the wheat images as the feature, and the linear model as the learning algorithm, we achieved a False Positive Rate (1-specificity) of 0.2 at the True Positive Rate (sensitivity) of 0.8 and an Area Under the ROC Curve (AUC) of 0.86. Combining the linear model and a Radial Basis Function Network in a committee resulted in a FP Rate of 0.1 at the TP Rate of 0.8 and an AUC of 0.92.
      Keywords
      Image transmittance
      Kernels
      Pixel intensity
      Radial function networks
      Algorithms
      Computer simulation
      Markov processes
      Mathematical models
      Mobile telecommunication systems
      Robustness (control systems)
      Sensors
      Image processing
      Permalink
      http://hdl.handle.net/11693/27406
      Published Version (Please cite this version)
      https://doi.org/10.1109/ICIP.2004.1421723
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      • Department of Electrical and Electronics Engineering 3524
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