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A distributed CBIR system based on DCNN on Apache Spark and Alluxio
Author(s): Chen Li; Linhua Jiang; Xiaodong Chen
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Paper Abstract

In the face of massive image data, how to improve the speed of image retrieval under the premise of ensuring accuracy is the focus of this research. In this paper, a distribute CBIR system based on the deep convolutional neural networks (DCNN) on Spark and Alluxio is proposed. Spark platform is a distributed memory calculation model to achieve higher computing performance. Alluxio is a high-performance, fault-tolerant, memory-based open source distributed storage system. This article lets Spark focus on computing image features and image matching. The storage of intermediate data in the image matching process is handled by Alluxio, thus breaking the bottleneck of Spark computing. The results of a large number of comparative experiments show that the proposed system shows obvious advantages both in terms of image storage capability and image retrieval speed.

Paper Details

Date Published: 29 October 2018
PDF: 6 pages
Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 108360L (29 October 2018); doi: 10.1117/12.2514230
Show Author Affiliations
Chen Li, Univ. of Shanghai for Science and Technology (China)
Linhua Jiang, Univ. of Shanghai for Science and Technology (China)
Xiaodong Chen, Shanghai Advanced Research Institute (China)


Published in SPIE Proceedings Vol. 10836:
2018 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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