Study on color image processing based intelligent fruit sorting system

A machine vision system that can be used for automatic high-speed fruit sorting is proposed. Fruit area was first segmented out from image with an Ohta-color-space based thresholding algorithm; blob algorithm was utilized to remove noises in image; spline-interpolation based algorithm was adopted to detect fruit contour. In fruit sorting process, fruit's color ratio, which was calculated with HSI color space, was selected as classification feature. Fruit sorting was realized by classic Bayes classifier, whose parameters were obtained by a study module. This system was tested with Crystal Fuji apples, and an average sorting accuracy of 90% was achieved.