Aiming at the complexity and anisotropy of the color and texture of colored spun fabrics images that are difficult to be accurately described by a single feature,a color spun fabrics image retrieval algorithm based on Transformer network feature fusion was proposed.First,the high-level semantic information of colored spun fabrics was extracted by using the convolutional neural network model;then,the third-order color moment features of the image wewere fused by using the Transformer network to make full use of the complementarity between the ＂ high-level semantic information＂ and the ＂ low-level semantic information＂ of colored spun fabrics for image retrieval.Then,the third-order color moment features were fused using the Transformer network to make full use of the complementary nature of＂high-level semantic information＂ and ＂low-level semantic information＂ of color textile images for image retrieval.In this paper,14 different types of color-spun knitted fabric sample images were used for retrieval,and the Top-10 recall and mAP of this system reach 98.35%and 89.25%,respectively,which is an improvement in the recall and mAP of retrieving Top-10 compared to a single network model incorporating an attention mechanism.
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