Microservices architecture for feature extraction in content-based image retrieval systems

被引:0
作者
Ruiz Velasco, Andres Felipe [1 ]
Roa Martinez, Sandra Milena [1 ]
机构
[1] Univ Cauca, Popayan, Colombia
关键词
CBIR Architecture; Microservices; Feature Extraction; Google Cloud; Image Retrieval; SERVICE SAAS MODEL; CLOUD; CBIR; FRAMEWORK; SOFTWARE;
D O I
10.17981/ingecuc.16.2.2020.15
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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. Objective: 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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页数:12
相关论文
共 17 条
[1]   Microservices Architecture Enables DevOps Migration to a Cloud-Native Architecture [J].
Balalaie, Armin ;
Heydarnoori, Abbas ;
Jamshidi, Pooyan .
IEEE SOFTWARE, 2016, 33 (03) :42-52
[2]  
Becker M, 2015, P 6 ACMSPEC INT C PE, DOI 10.1145/2668930.2688043
[3]  
Cerny Tomas., 2017, P INT C RES ADAPTIVE, P228, DOI [10.1145/3129676.31296825, DOI 10.1145/3129676.31296825]
[4]   Content Based Image Retrieval with Enhanced Privacy in Cloud Using Apache Spark [J].
Easwaramoorthy, Sathishkumar ;
Moorthy, Usha ;
Kumar, Chunduru Anil ;
Bhushan, S. Bharath ;
Sadagopan, Vishnupriya .
DATA SCIENCE ANALYTICS AND APPLICATIONS, DASAA 2017, 2018, 804 :114-128
[5]   Multilayer Architecture for Content-based Image Retrieval Systems [J].
Grycuk, Rafal ;
Najgebauer, Patryk ;
Nowicki, Robert ;
Scherer, Rafal .
2019 IEEE 12TH CONFERENCE ON SERVICE-ORIENTED COMPUTING AND APPLICATIONS (SOCA 2019), 2019, :119-126
[6]   Content-Based Image Retrieval in Augmented Reality [J].
Kaliciak, Leszek ;
Myrhaug, Hans ;
Goker, Ayse .
AMBIENT INTELLIGENCE- SOFTWARE AND APPLICATIONS- 8TH INTERNATIONAL SYMPOSIUM ON AMBIENT INTELLIGENCE (ISAMI 2017), 2017, 615 :95-103
[7]   Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review [J].
Latif, Afshan ;
Rasheed, Aqsa ;
Sajid, Umer ;
Ahmed, Jameel ;
Ali, Nouman ;
Ratyal, Naeem Iqbal ;
Zafar, Bushra ;
Dar, Saadat Hanif ;
Sajid, Muhammad ;
Khalil, Tehmina .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2019, 2019
[8]   Architecture for Software as a Service (SaaS) Model of CBIR on Hybrid Cloud of Microsoft Azure [J].
Meena, Mamta ;
Singh, Anamika Ram ;
Bharadi, Vinayak A. .
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMMUNICATION, COMPUTING AND VIRTUALIZATION (ICCCV) 2016, 2016, 79 :569-578
[9]   Hybrid Wavelet Based CBIR System using Software as a Service (SaaS) Model on public Cloud [J].
Meena, Mamta ;
Bharadi, Vinayak A. ;
Vartak, Krunali .
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMMUNICATION, COMPUTING AND VIRTUALIZATION (ICCCV) 2016, 2016, 79 :278-286
[10]   Gray level co-occurrence matrix and random forest based acute lymphoblastic leukemia detection [J].
Mishra, Sonali ;
Majhi, Banshidhar ;
Sa, Pankaj Kumar ;
Sharma, Lokesh .
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2017, 33 :272-280