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Aiming at the lack of effective methods for the quantification and uncertainty evaluation of small defects in industrial CT systems, the effects of small defect size and material density on the local grayscale variation coefficient of CT images are analyzed. The correlation between the amplitude of the coefficient of variation and the size of the small defect is explored. The results show that the local variation coefficient increases with the increase of the size of the small defect, and the correlation coefficient between its amplitude and the size of the small defect is more than 99%. Establish a small defect quantification and uncertainty evaluation method based on the coefficient of variation. This method verifies the known through-hole defect of Ф0.7mm on a Ф50mm circular contrast sample. The actual measurement result is 0.386mm_² ± 0.073 mm_². This method has high quantitative accuracy and simple measurement process. It has certain reference value for the quantification and uncertainty evaluation of small defects in metal materials.