Método multimodal de microscopía óptica para la detección de defectos en arreglos de topes de indio basado en la diferencia del campo de deformación de Demons multiescala

Persistent challenges in indium bump defect detection for infrared focal plane array (IRFPA) include low detection accuracy and high false-positive rates caused by subtle deformations from process variations, imaging distortions and scale variations in microscopic imaging. To address these shortcomings, this paper proposes a defect detection method based on the multi-scale Demons deformation field difference. A workflow comprising global coarse registration, local deformation field optimisation, and adaptive defect segmentation was established. Leveraging a multi-scale Bilateral Total Variation (BTV)-regularised Demons model, we progressively refined local details through hierarchical deformation field computation. This approach suppressed noise-induced distortions while preserving abrupt transitions, which helps to improve the saliency of local defect signals. The method shows improved robustness against deformation, noise, and scale variations compared to conventional template-matching algorithms. It is designed to meet the requirements for industrial inspection and provides a framework for weak-feature extraction and precise defect identification across multiple imaging modalities-including wide-field, bright-field confocal, and dark-field confocal microscopy.