Abstract
This paper is an attempt to design a fast image retrieval system with limited hardware resources. To this end, we use two-stage color-based features, Hadoop with HDFS to ensure file system flexibility, even in the case of sprawling into cloud projects and JAVA environment to run on every operating system. Namely, we retrieve images by color histogram and then by the color coherence vector to pick the best match from the results found by the previous algorithm. We tested the system on a large set of Microsoft COCO images.
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Acknowledgements
This work was supported by the Polish National Science Centre (NCN) within project number DEC-2011/01/D/ST6/06957.
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Łagiewka, M., Scherer, R., Angryk, R. (2016). Color-Based Large-Scale Image Retrieval with Limited Hardware Resources. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_61
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DOI: https://doi.org/10.1007/978-3-319-39384-1_61
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