Innovative reliable nanoscale QCA circuits for advanced morphological image processing

Quantum-dot cellular automata (QCA) technology has emerged as a promising alternative to conventional VLSI, offering benefits such as minimal power consumption, rapid switching, and a remarkably compact circuit footprint. These properties make QCA particularly suitable for designing nano-scale circuits in advanced image processing applications. Morphological operations, a prominent part of image processing, are widely utilized for tasks such as image enhancement, object recognition, medical imaging, and autonomous systems. However, existing QCA-based circuits for such operations face limitations in speed, accuracy, and resource efficiency, necessitating novel and optimized designs. This research introduces a new, reliable QCA architecture designed for morphological operations in image processing. The proposed design incorporates two majority gates and a control line to seamlessly perform dilation and erosion. Through immediate interactions with QCA cells, the circuit achieves substantial enhancements in covered space, speed, efficiency, and quantum cost. Extensive simulations using QCADesigner and QCADesigner-E validate the circuit’s performance, demonstrating its capability to produce accurate results with fault tolerance while minimizing energy depletion. Comparative analyses highlight the proposed architecture outperforming existing QCA circuits. These advancements position the design as a robust and efficient solution for next-generation image processing applications, with potential applications in medical imaging, facial recognition, and autonomous vehicle systems.