HiRes: A Hierarchical Cascaded Method for Resistor Value Identification
Accurate identification of resistor values from unconstrained images remains a challenging computer vision task due to variations in lighting, orientation, scale, and background complexity. This paper presents HiRes, a hierarchical cascaded pipeline for end-to-end resistor value identification directly from full-frame images. The approach combines object detection (YOLOv8n), semantic segmentation (UNet++ with EfficientNet-B2), and structured geometric decoding via projection along the resistor axis. To improve robustness, we incorporate geometric filtering, gap-preserving band separation, and validation against the E24 resistor series. Experiments across diverse real-world images show tha...
| Authors | Rama Y. AlHamidi, Aseel A. Mohamed, Mustafa A. Eltayeb et al. |
|---|---|
| Primary category | cs.CV |
| Published | 29 June 2026 |
| Last updated at source | 29 June 2026 |
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