Hue Correction Model Of Machine Vision System And Application In Citrus Color Grading

In the process of color inspection and automatic grading of fruits with machine vision, the quality of fruit image captured by cameras would influences the accuracy of inspection and grading directly. It is impossible to completely avoid the color distortion caused by the hardware of machine vision system and the illumination of lighting chamber, so if should be corrected with proper correction model. The laws of color distortion of the machine vision system were studied, the color distortion and correction model is set up, and the validity of model in fruit color grading is proved. Main contents and results were as follows:The research advancements and achievements in the area of nondestructive inspection of fruit quality and automatic grading with machine vision were reviewed, and the existing problems were put forward.Machine vision system suitable for this research was Set up . This system is composed of Meter II / MC ( Matrox.Inc. ) image grabber, TMC-7DSP (PULNIX) CCD and 6 F40BX/840 (GE) fluorescent lamps.Hue of flat cards got form machine vision system and color meter was compared. Law of hue distortion with machine vision system was analysed and hue correction model was set up.hue of 27 flat card with different colors captured at 3 different positions was compared and hue correction model was set up. Position 0: y0 =1.0318x0-3.3828 , position 1: y1 =1.0336x1 -2.8485 , positions 2: y2 =1.0304x2 -2.2285 . Model correlation coefficient R2 was 0.9817,0.9859 and 0.9890 respectively. Here, y0 , y1 , y2 and x0 , x1 , x2 were the hue value after and before correction at three position respectively.The sphere images of 10 balls were captured at 3 different positions as the flat cards. It is proved that curvature of object have no influence on hue distortion in this machine vision system, basically. So distorted hue of balls can be corrected by the model of corresponding position flat cards directly. This conclusion can be referenced by other machine vision system.Regarding hue value in HSV color model as index, hue of fruit surface ranges from 35° to 80°, which was divided into five areas with 10° intervals. Fruits were graded according to hue frequencies of [35°, 45°] [34°, 44°] and [36°, 46°] respectively .The best Result was got at area [36°, 46°].After correcting with hue distortion model at the corresponding position, the grading accuracies of grade 1, grade 2, grade 3 and substandard fruit were 100%, 75.00%, 75.00% and 100% respectively while 71.43%, 73.33%,46.67% and 100% respectively before correction.It was proved that the hue correction model and way with machine vision system were effective.