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Locality sensitive hashing for content based image retrieval: A comparative experimental study
- Source :
- Proceedings NGNS 2014 : 5th International Conference on Next Generation Networks and Services, NGNS 2014 : 5th International Conference on Next Generation Networks and Services, NGNS 2014 : 5th International Conference on Next Generation Networks and Services, May 2014, Casablanca, Morocco. pp.38-43, ⟨10.1109/NGNS.2014.6990224⟩
- Publication Year :
- 2014
- Publisher :
- IEEE, 2014.
-
Abstract
- International audience; This paper presents a comparative experimental study of the multidimensional indexing methods based on the approximation approach. We are particularly interested in the LSH family, which provides efficient index structures and solves the dimensionality curse problem. The goal is to understand the performance gain and the behavior of this family of methods on large-scale databases. E2LSH is compared to the KRA+-Blocks and the sequential scan methods. Two criteria are used in evaluating the E2LSH performances, namely average precision and CPU time using a database of one million image descriptors
- Subjects :
- Curse of dimensionality
Computer science
Scalability
CPU time
computer.software_genre
Content-based image retrieval
Locality-sensitive hashing
Full table scan
Multidimensional indexing
Content based image retrieval (CBIR)
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Index (publishing)
Locality sensitive hashing
Visual Word
Data mining
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2014 International Conference on Next Generation Networks and Services (NGNS)
- Accession number :
- edsair.doi.dedup.....6f8746ccf998e89d8624a58da908270a
- Full Text :
- https://doi.org/10.1109/ngns.2014.6990224