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A parallel content-based image retrieval system using spark and tachyon frameworks
- Source :
- Journal of King Saud University: Computer and Information Sciences, Vol 33, Iss 2, Pp 141-149 (2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- With the huge increase of large-scale multimedia over Internet, especially images, building Content-Based Image Retrieval (CBIR) systems for large-scale images has become a big challenge. One of the drawbacks associated with CBIR is the very long execution time. In this article, we propose a fast Content-Based Image Retrieval system using Spark (CBIR-S) targeting large-scale images. Our system is composed of two steps. (i) image indexation step, in which we use MapReduce distributed model on Spark in order to speed up the indexation process. We also use a memory-centric distributed storage system, called Tachyon, to enhance the write operation (ii) image retrieving step which we speed up by using a parallel k-Nearest Neighbors (k-NN) search method based on MapReduce model implemented under Apache Spark, in addition to exploiting the cache method of spark framework. We have showed, through a wide set of experiments, the effectiveness of our approach in terms of processing time.
- Subjects :
- Spark
CBIR
Speedup
General Computer Science
Computer science
CBIR-S
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Process (computing)
020206 networking & telecommunications
02 engineering and technology
Parallel k-NN
Content-based image retrieval
lcsh:QA75.5-76.95
Set (abstract data type)
Computer engineering
Spark (mathematics)
Distributed data store
0202 electrical engineering, electronic engineering, information engineering
Cache method
020201 artificial intelligence & image processing
Tachyon
lcsh:Electronic computers. Computer science
Cache
Image retrieval
Subjects
Details
- ISSN :
- 13191578
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- Journal of King Saud University - Computer and Information Sciences
- Accession number :
- edsair.doi.dedup.....4d483c11b1ab049d4c65a13981a2fed4