Image retrieval of colored spun fabrics based on decoupled feature

Aiming at a single feature is difficult to accurately describe the complexity and anisotropy of color and texture of colored spun fabric images, and the color and texture of images may affect each other. A colored spun fabric image retrieval method based on decoupled feature is proposed. The color templates and texture templates of the images are extracted and decoupled; at the same time, deep hash coding is used to calculate the similarity; finally, the preliminary retrieval results are reordered using the decoupled feature. In this paper, seven different types of colored spun fabric sample images are used for retrieval, and the Top-10 recall and mAP of this system reach 95.00% and 86.56%, respectively, which improves the recall and mAP of retrieving Top-10 compared to the methods without feature decoupling and those with feature decoupling only for a single feature.