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A Fast and Scalable Image Retrieval Algorithms by Leveraging Distributed Image Feature Extraction on MapReduce
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  • Journal title : Journal of KIISE
  • Volume 42, Issue 12,  2015, pp.1474-1479
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2015.42.12.1474
 Title & Authors
A Fast and Scalable Image Retrieval Algorithms by Leveraging Distributed Image Feature Extraction on MapReduce
Song, Hwan-Jun; Lee, Jin-Woo; Lee, Jae-Gil;
With mobile devices showing marked improvement in performance in the age of the Internet of Things (IoT), there is demand for rapid processing of the extensive amount of multimedia big data. However, because research on image searching is focused mainly on increasing accuracy despite environmental changes, the development of fast processing of high-resolution multimedia data queries is slow and inefficient. Hence, we suggest a new distributed image search algorithm that ensures both high accuracy and rapid response by using feature extraction of distributed images based on MapReduce, and solves the problem of memory scalability based on BIRCH indexing. In addition, we conducted an experiment on the accuracy, processing time, and scalability of this algorithm to confirm its excellent performance.
MapReduce;feature extraction;image retrieval;distributed computing;
 Cited by
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