Automatic visual inspection of corn kernels using principal component analysis

This paper presents an approach that combines algorithm-based computer vision techniques and principle component analysis (PCA) to eliminate poor quality corn kernels. Experiments show that the method is promising (89% success) but extensions are recommended to further improve results.