Research on embroidery image recognition based on deep learning

Yinglu Wu

doi:10.1117/12.3005861

10 October 2023 Research on embroidery image recognition based on deep learning

Yinglu Wu

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127991U (2023) https://doi.org/10.1117/12.3005861
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

In image recognition, Faster R-CNN detection algorithm based on R-CNN has received more and more attention in recent years. Compared with traditional image processing algorithms, this type of algorithm can extract deeper pattern features in complex embroidery images and improve the robustness and recognition accuracy of the algorithm. In order to extract deeper pattern features in embroidery images, this paper uses Faster R-CNN networks to recognize different types of embroidery patterns, and uses ResNet50 and VGG16 as Faster R-CNN feature extraction networks respectively for comparison. The experimental results show that the Faster R-CNN network based on ResNet50 has better image recognition effect after pre-training.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yinglu Wu "Research on embroidery image recognition based on deep learning", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127991U (10 October 2023); https://doi.org/10.1117/12.3005861

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