Image-processing algorithms for tomato classification Academic Article uri icon

abstract

  • Image–processing algorithms were developed and implemented to provide the following quality parameters for tomato classification: color, color homogeneity, defects, shape, and stem detection. The vision system consisted of two parts: a bottom vision cell with one camera facing upwards, and an upper vision cell with two cameras viewing the fruit at 60º. The bottom vision cell determined fruit stem and shape. The upper vision cell determined fruit color, defects, and color homogeneity. Experiments resulted in 90% correct bruise classification with 2% severely misclassified; 90% correct color homogeneity classification; 92% correct color detection with 2% severely misclassified, and 100% stem detection.

publication date

  • January 1, 2002