Artículo

An Efficient Content Based Image Retrieval using EI Classification and Color Features

Yasmin, M.; Sharif, M.; Irum, I.; Mohsin, S.

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology ( (Revistas UNAM)

Licencia de uso

La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx. Ver términos de la licencia

Procedencia del contenido

Cita

Yasmin, M., et al. (2014). An Efficient Content Based Image Retrieval using EI Classification and Color Features. Journal of Applied Research and Technology; Vol. 12 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/45749

Descripción del recurso

Autor(es)
Yasmin, M.; Sharif, M.; Irum, I.; Mohsin, S.
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
An Efficient Content Based Image Retrieval using EI Classification and Color Features
Fecha
2014-10-01
Resumen
An efficient method for image search and retrieval has been proposed in this study. For this purpose images aredecomposed in equal squares of minimum 24x16 size and then edge detection is applied to those decomposed parts.Pixels classification is done on the basis of edge pixels and inner pixels. Features are selected from edge pixels forpopulating the database. Moreover, color differences are used to cluster same color retrieved results. Precision andrecall rates have been used as quantification measures. It can be seen from the results that proposed method showsa very good balance of precision and recall in minimum retrieval time, achieved results are comprised of 66%-100%rate for precision and 68%-80% for recall.
Tema
Color Distances; Edge Pixels; Feature Extraction; Image Clustering; Inner Pixels
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423
DOI
https://doi.org/10.1016/S1665-6423(14)70594-2

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