@Article{JFBI-9-29,
author = {Liqing Xie, Yue Shen and Xiaozhi Chen},
title = {Study on Automatic Recognition of Fabric Color and Matching to Standard Color Chip by Computer Vision and Image Analysis Technology},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2016},
volume = {9},
number = {1},
pages = {29--37},
abstract = {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.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbim00194},
url = {http://global-sci.org/intro/article_detail/jfbi/10589.html}
}