To achieve accuracy when customizing knitted products, the size parameters of various parts of the user's body, such as arm length and waist circumference, are obtained via manual measurement or three-dimensional scanning. However, for customized products such as medical socks, which have high-precision design requirements, the existing customization design methods can only ensure the accuracy of key data, such as foot length and foot height, but cannot meet the requirements for all-round customization based on users' foot data. To improve design accuracy, this study proposes a method to generate automatically a continuous set of fine size parameters that are required for knitting from a three-dimensional model of socks based on the idea of simulated knitting. Specifically, a region segmentation method based on the shape diameter function and model skeleton is developed. The sock model is divided into regions such as heel, foot, and toe, which correspond to the knitting process. In addition, a method to simulate the knitting process of a sock machine is developed, which enables loop-by-loop knitting using a sock machine via layer-by-layer iterative sampling on the surface of the model. The sampling axis is generated based on the model skeleton as the direction of sock knitting for the simulation. In the process of simulating knitting, the knitting method is switched between the divided area. Then, the knitting path of the yarn and the parameters required for the simulated sock machine that meet the sock-making process conditions are obtained. Finally, actual socks are knitted using the machine with the obtained knitting parameters, and the proportion of each area of the socks is compared with that of the model. The error is less than 6%. The proposed method can improve the production accuracy of customized socks, which is of great significance for improving the three-dimensional molding technology of socks.