In this work, we explore a novel edge detection method based on a Quantum Fuzzy Inference Engine implemented on a real quantum computer. We address an industrial defect detection problem using a proprietary fruit dataset. Our approach combines a hybrid quantum-classical lookup table for edge detection with a classical contour tracking algorithm and is compared against state-of-the-art classical methods. Our hybrid model achieves comparable precision to its classical counterpart while requiring fewer operations. Moreover, comparisons with other leading classical techniques confirm the reliability of our approach, as it delivers very similar results.
Quantum Fuzzy Edge Detection Algorithm: An Industrial Application
Nunziata G.;Coraggio L.;Crisci S.;De Gregorio G.;Itaco N.;
2025
Abstract
In this work, we explore a novel edge detection method based on a Quantum Fuzzy Inference Engine implemented on a real quantum computer. We address an industrial defect detection problem using a proprietary fruit dataset. Our approach combines a hybrid quantum-classical lookup table for edge detection with a classical contour tracking algorithm and is compared against state-of-the-art classical methods. Our hybrid model achieves comparable precision to its classical counterpart while requiring fewer operations. Moreover, comparisons with other leading classical techniques confirm the reliability of our approach, as it delivers very similar results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
