USP Electronic Research Repository

Quantum classifier for recognition and identification of leaf profile features

Kumar, Amit K. and Mai, Nguyễn N. and Kumar, Ashmit and Chand, Nividita V. and Assaf, Mansour (2022) Quantum classifier for recognition and identification of leaf profile features. The European Physical Journal D, 76 (110). NA. ISSN 1434-6060

Full text not available from this repository.

Abstract

Quantum-based classifiers and architecture are gaining lots of attention in image representation and cryptography. The proposed algorithm applies a quantum classifier to a computer vision system for leaf recognition which can be applied to a quantum computer. Images from ten species of leaves which are categorised into two groups, namely simple and palmately, are recognised using a quantum classifier. The pixels of images are transformed to qubit states using quantum Fourier transform (QFT) and Hadamard gates. The profile and structural features are extracted by applying 1D-convolution and controlled not (CNOT) gates. A quantum nearest neighbour search classifier is used to find the closest matching leaf based on probability. The results for different levels of image processing are evaluated and compared with the nearest neighbour classifier. The recognition rate of the quantum classifier for the best level of image processing is 97.33%. The recognition rate of the classifier is better than the nearest neighbour classifier and also has a low computation time.

Item Type: Journal Article
Subjects: Q Science > QC Physics
T Technology > T Technology (General)
Divisions: School of Information Technology, Engineering, Mathematics and Physics (STEMP)
Depositing User: Mansour Assaf
Date Deposited: 04 Jul 2022 22:29
Last Modified: 04 Jul 2022 22:29
URI: http://repository.usp.ac.fj/id/eprint/13517
UNSPECIFIED

Actions (login required)

View Item View Item