Towards Pixel-Wise Anomaly Location for High-Resolution PCBA via Self-Supervised Image Reconstruction

• URL: http://arxiv.org/abs/2512.17296v2
• Date: Mon, 22 Dec 2025 02:49:56 GMT
• Title: Towards Pixel-Wise Anomaly Location for High-Resolution PCBA via Self-Supervised Image Reconstruction
• Abstract summary: HiSIR-Net is a High resolution, Self-supervised Reconstruction framework for pixel-wise PCBA localization.<n>Our design combines two lightweight modules that make this practical on real 4K-resolution boards.<n>To bridge the gap in high-resolution PCBA datasets, we contribute a self-collected dataset named SIPCBA-500 of 500 images.
• Score: 16.925545387541653
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Automated defect inspection of assembled Printed Circuit Board Assemblies (PCBA) is quite challenging due to the insufficient labeled data, micro-defects with just a few pixels in visually-complex and high-resolution images. To address these challenges, we present HiSIR-Net, a High resolution, Self-supervised Reconstruction framework for pixel-wise PCBA localization. Our design combines two lightweight modules that make this practical on real 4K-resolution boards: (i) a Selective Input-Reconstruction Gate (SIR-Gate) that lets the model decide where to trust reconstruction versus the original input, thereby reducing irrelevant reconstruction artifacts and false alarms; and (ii) a Region-level Optimized Patch Selection (ROPS) scheme with positional cues to select overlapping patch reconstructions coherently across arbitrary resolutions. Organically integrating these mechanisms yields clean, high-resolution anomaly maps with low false positive (FP) rate. To bridge the gap in high-resolution PCBA datasets, we further contribute a self-collected dataset named SIPCBA-500 of 500 images. We conduct extensive experiments on our SIPCBA-500 as well as public benchmarks, demonstrating the superior localization performance of our method while running at practical speed. Full code and dataset will be made available upon acceptance.

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