Detection of navel surface defects based on illumination-reflectance model

The presence of skin defects is one of the main influential factors on the price of fruit. Most of the researches used static images and more complex algorithm to segment defects on fruit surface. The lighting correction approach and threshold method was proposed to segment fruit surface defects. The fruit images with defects were acquired from an on-line sorting system. Firstly, hue (H) component was obtained by transforming RGB colour space to HIS colour space. The mask was created based on H component and used to remove R component image background. Then, based on illumination-reflectance model, the illumination component was extracted from R component image by low pass filter. The illumination component was used to correct illumination on R-component image. Finally, defects were successfully segmented at one time by subjecting the corrected image to a single threshold value. The experimental results with an over 99% recognition rate for 416 images showed that the proposed algorithm was simple and effective for application in real-time detection of defects on fruit.