Curling is a common phenomenon observed in knitted fabrics. Curling poses many problems for fabric and clothing production, especially for digital devices, where it can affect the production quality and efficiency, while there is still no accurate method for evaluating it. This study established an evaluation method for the curling properties of knitted fabrics based on pixel statistics. Weft knitted fabric samples were created using a fabric cutter and a piece of paper was placed underneath the fabric. The fabric sample curls, whereas the paper represents a non-curling state. Subsequently, a scanner was used to scan the projections of the circular samples and paper to obtain digital images. The pixel amounts of the curled fabric and paper digital images were measured using the Photoshop 2020 software. The ratio between the fabric and paper projection pixels can be calculated by subtracting from 100% and converting the curling area ratio to the curling distance ratio. This can be used to represent the curling properties of knitted fabrics. The error between the theoretical and measured values is <0.1%, indicating a high level of accuracy. Ten knitted fabrics were validated for analysis. The sample with the maximum deviation between the left, middle, and right positions was 5.9%, whereas that with the minimum deviation was 0.3%. Subsequently, the fabrics were retested on the 7th and 14th days to assess reproducibility. The maximum deviation for each fabric on the 1st, 7th, and 14th days was 4.1%, and the minimum deviation was 0%. Therefore, it can be concluded that the method described in this study can accurately quantify the curling properties of knitted fabrics.