This paper aims at investigating the ancient Chinese textile in order to facilitate the growing trend of an interdisciplinary study between art history, industrial design and imaging science. This is an early attempt to study how decorative patterns of the textiles were created with various weaving techniques with the help of digital technology. Since the captured fabric image only reveals the floating yarn, the combination of the underneath yarns are unknown. From the mathematical point of view, the weaving technique can be regarded as a research problem of combinatorics that contains how the yarns of weft and warp intersect with each other. Hence, the analysis of the weaving pattern contains two layers: (a) detection of the floating yarn and (b) estimation of the combination of the underneath yarns. Previously, the regular bands (RB) method is a tool for regularity analysis that has been successfully applied to patterned fabric inspection. This paper achieves the first layer goal, which applies computer vision technique in the imaging science through the RB method to achieve the detection of the floating yarns of images of some ancient Chinese textiles. Ancient textile samples from Ming dynasty, China (ca. 1368-1644 CE) are utilized for the experiments in the paper.
Connie C.W. Chan, K.S. (Sammy) Li, Henry Y.T. Ngan, "Weaving Pattern Recognition of Ancient Chinese Textiles by Regular Bands Analysis" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Intelligent Robotics and Industrial Applications using Computer Vision, 2017, pp 31 - 36, https://doi.org/10.2352/ISSN.2470-1173.2017.9.IRIACV-263