This research focuses on the improvement of intelligent Hanfu design system’s performance. Henceforth, in the current study, an intelligent Hanfu design data acquisition system based on scientific graphics programming and wearable multisensor is designed for the field of human body size measurement and human model reconstruction. Initially, on the basis of wearable multisensor, a design of the recognition and analysis system of human posture is presented. The error of nine-axis inertial sensor in the process of collecting data, the data of accelerometer, gyroscope, and magnetometer are preprocessed, and the processing results are observed. Moreover, MATLAB programming is used for preprocessing of collected images. It is also used for grey normalization, filtering denoising, and image sharpening. The advantages and disadvantages of different methods are compared experimentally. Experiments show that MATLAB programming is more suitable for grey normalization than histogram equalization, and local brightness will appear in histogram equalization. After denoising the image with salt-and-pepper noise and Gaussian noise, the median filter and mean filter have defects. Wiener’s adaptive filter leads to the increase of noise, and wavelet denoising has the best effect. The data acquisition system of intelligent Hanfu design established in this work provides a certain direction for the development of intelligent Hanfu design.