Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/345363
Type: Artigo
Title: Continuous-valued quaternionic Hopfield neural network for image retrieval: a color space study
Author: Castro, Fidelis Zanetti de
Valle, Marcos Eduardo
Abstract: Continuous-valued quaternionic Hopfield neural network (CV-QHNN) generalizes the traditional Hopfield network for the storage and retrieval of vectors whose components are unit quaternions. In this paper, we investigate the performance of the CV-QHNN for the retrieval of color images using three different color spaces: RGB, HSV, and CIE-HCL. We point out that a direct conversion from the RGB to unit quaternions may result distortions in which visually different colors are mapped into close quaternions. Preliminary computational experiments reveal that the CV-QHNN based on the HSV color space can be more effective for the removal of noise from a corrupted color image.
Subject: Quatérnios
Hopfield
Redes neurais de
Memória associativa
Processamento de imagens
Inteligência computacional
Quaternions
Hopfield neural networks
Associative memory
Image processing
Computational intelligence
Country: Estados Unidos
Editor: American Institute of Mathematical Sciences
Rights: fechado
Identifier DOI: 10.1109/BRACIS.2017.52
Address: https://ieeexplore.ieee.org/document/8247051
Date Issue: 2017
Appears in Collections:IMECC - Artigos e Outros Documentos

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