A Fast Quantum Image Component Labeling Algorithm - Yan Li; Dapeng Hao; Yang Xu; Kinkeung Lai (Mathematics, 2022)
Component Labeling, as a fundamental preprocessing task in image understanding and pattern recognition, is an indispensable task in digital image processing. It has been proved that it is one of the most time-consuming tasks within pattern recognition. In this paper, a fast quantum image component labeling algorithm is proposed, which is the quantum counterpart of classical local-operator technique. A binary image is represented by the modified novel enhanced quantum image representation (NEQR) and a quantum parallel-shrink operator and quantum propagate operator are executed in succession, to finally obtain the component label. The time complexity of the proposed quantum image component labeling algorithm is <semantics>O(n2)</semantics>, and the spatial complexity of the quantum circuits designed is <semantics>O(cn)</semantics>. Simulation verifies the correctness of results.