Title :
Identification of insect damaged wheat kernels using transmittance images
Author :
Cataltepe, Z. ; Enis Cetin, A. ; Pearson, Tim
Author_Institution :
Siemens Corp. Res. Inc., Princeton, NJ, USA
fDate :
3/3/2005 12:00:00 AM
Abstract :
Transmittance images of wheat kernels are used to classify insect damaged and undamaged wheat kernels. The colour histograms of pixel intensities of the wheat images were used as the feature vectors. Combination of the linear model and a radial basis function network, in a committee, resulted in a false positive rate of 0.1 at the true positive rate of 0.8 and an area under the receiver operating characteristics curve of 0.92.
Keywords :
agriculture; feature extraction; food technology; image classification; image colour analysis; radial basis function networks; area under receiver operating characteristics curve; colour histograms; committee-based model combination; damaged wheat kernel identification; damaged/undamaged wheat kernel classification; false positive rate; feature extraction; infested wheat kernels; insect damaged wheat kernels; linear model; pixel intensity histogram; radial basis function network; transmittance images; true positive rate;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20047250
