Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and s...Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and sorting of some single-color fruits such as banana and plum. Fruit images were captured using a color digital camera with capturing direction of zero degree and under illuminant D65. It was observed that growing decay and time-aging made surface color changes in bruised parts of the object. 3D RGB and HSV color vectors as well as a single channel like H （hue）, S （saturation）, V （value） and grey scale images were applied for color quantization of the object. Results showed that there was a distinct threshold in the histogram of the S channel of images which can be applied to separate the object from its background. Moreover, the color change via the defect and time-aging is correctly distinguishable in the hue channel image. The effect of illumination, gloss and shadow of 3D image processing is less noticeable for hue data in comparison to saturation and value. The value of H channel was quantized to five groups based on the difference between each pixel value and the H value of a healthy object. The percentage of different degree of defects can be computed and used for grading the fruits.展开更多
For the typical color detects of polysilicon wafers, i.e., edge discoloration, color inaccuracy and color non-uniformity, a new integrated machine vision detection method is proposed based on an HSV color model. By tr...For the typical color detects of polysilicon wafers, i.e., edge discoloration, color inaccuracy and color non-uniformity, a new integrated machine vision detection method is proposed based on an HSV color model. By transforming RGB image into three-channel HSV images, the HSV model can efficiently reduce the disturbances of complex wafer textures. A fuzzy color clustering method is used to detect edge discoloration by defining membership function for each channel image. The mean-value classi- fying method and region growing method are used to identify the other two defects, respectively. A vision detection system is developed and applied in the produc- tion of polysilicon wafers.展开更多
Aluminum metallization using the sprayed coating for exhaust mild steel （MS） pipes of tractors is a standard practice for avoiding rusting. Patches of thin metal coats are prone to rusting and are thus considered as...Aluminum metallization using the sprayed coating for exhaust mild steel （MS） pipes of tractors is a standard practice for avoiding rusting. Patches of thin metal coats are prone to rusting and are thus considered as defects in the surface coating. This paper reports a novel configuration of the fiber optic sensor for on-line checking the aluminum metaUization uniformity and hence for defect detection. An optimally chosen high bright 440 nm BLUE LED （light-emitting diode） launches light into a transmitting fiber inclined at the angle of 60° to the surface under inspection placed adequately. The reflected light is transported by a receiving fiber to a blue enhanced photo detector. The metallization thickness on the coated surface results in visually observable variation in the gray shades. The coated pipe is spirally inspected by a combination of linear and rotary motions. The sensor output is the signal conditioned and monitored with RISHUBH DAS. Experimental results show the good repeatability in the defect detection and coating non-uniformity measurement.展开更多
文摘Machine vision has been recently utilized for quality control of food and agricultural products, which was traditionally done by manual inspection. The present study was an attempt for automatic defect detection and sorting of some single-color fruits such as banana and plum. Fruit images were captured using a color digital camera with capturing direction of zero degree and under illuminant D65. It was observed that growing decay and time-aging made surface color changes in bruised parts of the object. 3D RGB and HSV color vectors as well as a single channel like H （hue）, S （saturation）, V （value） and grey scale images were applied for color quantization of the object. Results showed that there was a distinct threshold in the histogram of the S channel of images which can be applied to separate the object from its background. Moreover, the color change via the defect and time-aging is correctly distinguishable in the hue channel image. The effect of illumination, gloss and shadow of 3D image processing is less noticeable for hue data in comparison to saturation and value. The value of H channel was quantized to five groups based on the difference between each pixel value and the H value of a healthy object. The percentage of different degree of defects can be computed and used for grading the fruits.
基金supported by the National Natural Science Foundation of China(Grant Nos.51205242,and 51075261)the Shanghai Science and Technology Innovation Action Plan,China(Grant No.13111102900)
文摘For the typical color detects of polysilicon wafers, i.e., edge discoloration, color inaccuracy and color non-uniformity, a new integrated machine vision detection method is proposed based on an HSV color model. By transforming RGB image into three-channel HSV images, the HSV model can efficiently reduce the disturbances of complex wafer textures. A fuzzy color clustering method is used to detect edge discoloration by defining membership function for each channel image. The mean-value classi- fying method and region growing method are used to identify the other two defects, respectively. A vision detection system is developed and applied in the produc- tion of polysilicon wafers.
文摘Aluminum metallization using the sprayed coating for exhaust mild steel （MS） pipes of tractors is a standard practice for avoiding rusting. Patches of thin metal coats are prone to rusting and are thus considered as defects in the surface coating. This paper reports a novel configuration of the fiber optic sensor for on-line checking the aluminum metaUization uniformity and hence for defect detection. An optimally chosen high bright 440 nm BLUE LED （light-emitting diode） launches light into a transmitting fiber inclined at the angle of 60° to the surface under inspection placed adequately. The reflected light is transported by a receiving fiber to a blue enhanced photo detector. The metallization thickness on the coated surface results in visually observable variation in the gray shades. The coated pipe is spirally inspected by a combination of linear and rotary motions. The sensor output is the signal conditioned and monitored with RISHUBH DAS. Experimental results show the good repeatability in the defect detection and coating non-uniformity measurement.
