DocumentCode :
1791720
Title :
Scalable solar image Retrieval with Lucene
Author :
Banda, Juan M. ; Angryk, Rafal A.
Author_Institution :
Montana State Univ., Bozeman, MT, USA
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
11
Lastpage :
17
Abstract :
In this work we present an alternative approach for large-scale retrieval of solar images using the highly-scalable retrieval engine Lucene. While Lucene is widely popular among text- based search engines, significant adjustments need to be made to take advantage of its fast indexing mechanism and highly-scalable architecture to enable search on image repositories. In this work we describe a novel way of representing image feature vectors in order to enable Lucene to perform search and retrieval of similar images. We compare our proposed method with other popular alternatives and provide commentary of the performance as well as the benefits and caveats of the proposed method.
Keywords :
Sun; astronomical image processing; content-based retrieval; image retrieval; search engines; Lucene; content-based image retrieval; image feature vectors; image repositories; search engines; solar image retrieval; Big data; Buildings; Feature extraction; Filtering; Image retrieval; Indexes; Servers; Astroinformatics; Big Data Mining; Content-Based Image Retrieval; Image Processing; Image Retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location :
Washington, DC
Type :
conf
DOI :
10.1109/BigData.2014.7004399
Filename :
7004399
Link To Document :
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