Microservices architecture for feature extraction in content-based image retrieval systems
DOI:
https://doi.org/10.17981/ingecuc.16.2.2020.15Keywords:
CBIR architecture, microservices, feature extraction, Google Cloud, image retrievalAbstract
Introduction— Content-based image retrieval systems allow users, using a reference image, to retrieve those similar to their query. In the conception of such systems for the Web, aspects related to the high volume of existing digital images must be considered, which generate problems during their processing in real time, specifically in the extraction of their visual features, the object of this investigation.
Objectives— Contribute to the mitigation of scalability, elasticity, availability and reliability problems presented by the module for extracting its visual characteristics from a content-based image retrieval system.
Methodology— The definition, design and implementation of a proposal for architecture based on microservices was carried out, followed by the execution of tests using simulation-based experiments for the evaluation of said proposal, presenting the respective analysis and discussion of the results provided by the indicator panel of the Google Cloud console.
Results— A microservices-based architecture where each algorithm / technique for extracting features from a digital image was implemented as a microservice under the Google Cloud infrastructure.
Conclusions— This architectural proposal supported by microservices favors its automatic scalability during the extraction of features from large volumes of images and can be used in the design and construction of other modules of a content-based image retrieval system.
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