Content-based automatic retinal image recognition and retrieval system / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 403-408, 2013.
Artigo
em Chinês
| WPRIM
| ID: wpr-234641
ABSTRACT
This paper is aimed to fulfill a prototype system used to classify and retrieve retinal image automatically. With the content-based image retrieval (CBIR) technology, a method to represent the retinal characteristics mixing the fundus image color (gray) histogram with bright, dark region features and other local comprehensive information was proposed. The method uses kernel principal component analysis (KPCA) to further extract nonlinear features and dimensionality reduced. It also puts forward a measurement method using support vector machine (SVM) on KPCA weighted distance in similarity measure aspect. Testing 300 samples with this prototype system randomly, we obtained the total image number of wrong retrieved 32, and the retrieval rate 89.33%. It showed that the identification rate of the system for retinal image was high.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Oftalmoscopia
/
Patologia
/
Padrões de Referência
/
Retina
/
Vasos Retinianos
/
Algoritmos
/
Processamento de Imagem Assistida por Computador
/
Análise Numérica Assistida por Computador
/
Reconhecimento Automatizado de Padrão
/
Armazenamento e Recuperação da Informação
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2013
Tipo de documento:
Artigo
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