Defects Detection of Lentinus Edodes Surface Based on Computer Vision Technology

The traditional artificial method of detecting defects on entinus edodes surface is normal less efficiency and easily vision tiredness.Therefore,it can not satisfy the demand of the modern industry production.This research attempted to detect entinus edodes surface defects based on computer vision technology.Firstly,RGB images of samples were acquired and B component images were extracted to build mask for removing G component images background.Then,edge light compensation and defects extraction method were applied to G component images removed background.Subsequently,the defected regions were marked and the characteristic parameters were extracted and selected.In order to prevent imaging system and ambient light,the ratio value between defected regions areas and total surface area of entinus edodes studied was used to identify defected entinus edodes from normal entinus edodes.Finally,a global threshold value with 0.0035 was used to detect all samples.The results showed that an accuracy of 94% and 97.3% was achieved for normal and defected samples based on developed algorithm,respectively.In this research,the overall classification success rate reached 96.5%.