End-to-end industrial small-scale defect recognition based on real-time detection transformer

Hao Zhong; Zixuan Zhou; Mingyuan Yang; Shanfeng Liu; Youmin Hu; Haifeng Wang

doi:10.1117/12.3038528

23 August 2024 End-to-end industrial small-scale defect recognition based on real-time detection transformer

Hao Zhong, Zixuan Zhou, Mingyuan Yang, Shanfeng Liu, Youmin Hu, Haifeng Wang

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132500U (2024) https://doi.org/10.1117/12.3038528
Event: 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Industrial defect recognition is a key part of product quality control. Small-scale defect recognition has become a difficult task in defect detection due to the weak and easy loss of recognizable features. To address this problem, this paper proposes an end-to-end small-scale defect detection algorithm based on RT-DETR (Real-Time DEtection TRansformer) model. First, we feed a shallow texture feature layer into the efficient hybrid encoder and optimize the cross-scale feature fusion module with RepC3 block to extract richer texture features for small-scale defects; Second, we utilize IoU-aware Query Selection for feature screening to ensure the reliability of the features input to the decoder for prediction; Finally, we conduct comparison experiments on the self-made WM-FSD dataset and HRIPCB dataset, and the experimental results demonstrate that our proposed method for small-scale defect recognition in different scenarios has obvious advantages in terms of precision, recall, and average precision.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hao Zhong, Zixuan Zhou, Mingyuan Yang, Shanfeng Liu, Youmin Hu, and Haifeng Wang "End-to-end industrial small-scale defect recognition based on real-time detection transformer", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132500U (23 August 2024); https://doi.org/10.1117/12.3038528

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KEYWORDS

Defect detection

Transformers

Feature fusion

Visual process modeling

Education and training

Feature extraction

Detection and tracking algorithms

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