The expression ability of a commercial textile simulator was investigated by simulating textile images taking into account the effect of yarn count, weave density, yarn types and weave. The performance of the simulator was investigated by evaluating and comparing impressions of real textiles and simulated images. The effect of pattern and textile color on the simulation performance was also studied. It was found that simulated images of textiles with more complicated and multicolored patterns were perceived to be more alike to the real textiles. Simulated images with large patterns were also evaluated and found to compare favorably to real textiles. Color was observed to have no effect on the impression of simulated textile images. Therefore, textile simulation in the textile trade is more effective on complex variations of textile patterns and colors.

This paper deals with the research on simulation design of traditional Chinese costumes in digital method. We take Chi-pao (Cheongsam), the Mandarin gown of the Qing Dynasty as the research object and conduct a comprehensive analysis of its structures, colors, patterns and other traditional crafts. Then a simulation digital design is made and cutting pieces are printed through digital printer. The finished product shows that the simulation of traditional costumes through this method is feasible to achieve satisfactory results. Thus, simulation design can be used as one of the ways to research, inherit and spread the traditional Chinese costumes.

The Artificial visual approach to detect fabric color is easy to be affected by light and experience. In order to overcome the shortcomings of errors, this paper presents a new method for matching between textile fabric color and standard color card automatically, and establishes the automatic matching system for 1925 kinds of Pantone TCX color swatches by using computer vision and image analysis. First, the scan images of Pantone TCX color were acquired, then we extracted effective color characteristic information from the images, and constructed the database of color features. Furthermore, we designed color layered model and matching model which based on `one to one' Support Vector Machine (SVM). Through parameter optimization and identify training for SVM model, the accuracy of color identifying is 96.89{\%}. Finally, we used 296 unknown color samples for verification, the accuracy is 98.85{\%}. The results show that the research provides an effective auxiliary tool objectively and quickly for color measurement.

In the paper, two kinds of Woven Heated Fabrics (WHFs) were prepared and evaluated.~WHFs were fabricated by integrated silver filaments into fabrics with the same interval distance, and silver paste was coated on the crossing points of some WHFs to decrease contact resistance. Subsequently, surface infrared temperature images and temperature simulated by finite element method were utilized to evaluate the performance of WHFs. Experimental results showed surface temperature of WHFs is non-linear correlation with time when voltage was loaded on two ends of WHFs, but the surface equilibrium temperature of WHFs is linear correlation with loaded voltage and power consumption. However, simulated surface temperature is highly consistent with the measured surface temperature of silver filaments by adjusting the Heat Transfer Convection Coefficient (HTCC) at different loaded voltage. WHFs have wide application prospect in Electric Heating Garment (EHG) in the future. Infrared temperature images and finite element simulation can decrease the cost and enhance design efficiency of WHFs.

Automatic identification of fabric structure is a vital area of research. The skewing phenomenon is inevitable during the scanning process, so the fabric skew correction method based on projection profile analysis is proposed. First, Butterworth low-pass filter is applied to remove noises after skew correction of the fabric image. Then, power spectrum is obtained by Fast Fourier Transform (FFT), in which the peaks are extracted from the vertical and horizontal direction, respectively. Finally, the reconstructed image is obtained via Inverse Fast Fourier Transform (IFFT) according to the peaks, so that the information of warp and weft can be separated to calculate the warp and weft density. Experimental results show that the accuracy of the skew correction can be controlled within [$-$1$^\circ$, 1$^\circ$], and the detection accuracy of yarn density can reach 98\%. The proposed method can accurately detect skew angle and density of woven and knitted fabrics.