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Fabric Image Feature Extraction Algorithm Based on InceptionV3 Transfer Learning

Abstrcat: Fabric image retrieval is of great value to the management of fabric image information in textile factories, but the diversity of fabric images makes it difficult to extract fabric image features during fabric retrieval. This paper proposes a fabric image feature extraction algorithm based on InceptionV3 transfer learning, which uses a pre-trained InceptionV3 neural network to perform transfer learning and fine-tune to extract fabric image features to build a feature database. The fabric retrieval experiment was carried out on the fabric image data set FID (Fabric Image Dataset). Experiments show that the algorithm can ameliorate the accuracy of fabric image feature extraction, with a retrieval accuracy of 84.5%. This feature extraction algorithm has practical application value.