Memorias de investigación
Artículos en revistas:
A scalable approach for content based image retrieval in cloud datacenter
Año:2013
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Abstract The emergence of cloud datacenters enhances the capability of online data storage. Since massive data is stored in datacenters, it is necessary to effectively locate and access interest data in such a distributed system. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These techniques cannot satisfy the requirements of content based image retrieval (CBIR). In this paper, we propose a scalable image retrieval framework which can efficiently support content similarity search and semantic search in the distributed environment. Its key idea is to integrate image feature vectors into distributed hash tables (DHTs) by exploiting the property of locality sensitive hashing (LSH). Thus, images with similar content are most likely gathered into the same node without the knowledge of any global information. For searching semantically close images, the relevance feedback is adopted in our system to overcome the gap between low-level features and high-level features. We show that our approach yields high recall rate with good load balance and only requires a few number of hops.
Internacional
Si
JCR del ISI
Si
Título de la revista
Information Systems Frontiers
ISSN
1387-3326
Factor de impacto JCR
0,851
Información de impacto
Volumen
6
DOI
10.1007/s10796-013-9467-0
Número de revista
1
Desde la página
129
Hasta la página
141
Mes
SIN MES
Ranking
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Participantes
  • Autor: Jianxin Liao
  • Autor: Di Yang
  • Autor: Tonghong Li UPM
  • Autor: Jingyu Wang
  • Autor: Qi Qi
  • Autor: Xiaomin Zhu
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Laboratorio de sistemas distribuidos (LSD)