A Fast Quantum Image Component Labeling Algorithm
Yan Li, Da-peng Hao, Yang Xu, Kin Keung 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 O(n2), and the spatial complexity of the quantum circuits designed is O(cn). Simulation verifies the correctness of results.