Work

A Fast Quantum Image Component Labeling Algorithm

Year: 2022

Type: article

Abstract: 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.

Source: Mathematics

DOI: 10.3390/math10152718

Authors: Yan Li, Dapeng Hao, Yang Xu, Kinkeung Lai

Institutions: Xi'an Eurasia University, Xi'an Aeronautical University, Xi'an Technological University, University of Hong Kong

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,885

OpenAlex ID: W4289313541

FWCI: 0.199

Cites: 49

Cited by: 3

Related to: 10