Morphological edge detector implemented in Quantum Cellular Automata

Non-linear morphological edge detectors have been proven to be robust in the presence of noise and able to discriminate between edges and regions corrupted by noise. In this paper a novel non-linear morphological edge detector is presented when implemented as a compact circuit on Quantum Cellular Automata (QCA) in crossbar nanoelectronic architecture. The proposed QCA implementation provides high circuit performance, very low dimensions, parallel processing and very low power consumption. Moreover, the presented QCA circuit design obeys with the QCA design rules while focusing on circuit functionality robustness and thereafter provides real time image processing. The corresponding simulation results indicate the efficiency of the proposed circuitry.