{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T10:23:51Z","timestamp":1771237431198,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T00:00:00Z","timestamp":1560470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The process of image retrieval presents an interesting tool for different domains related to computer vision such as multimedia retrieval, pattern recognition, medical imaging, video surveillance and movements analysis. Visual characteristics of images such as color, texture and shape are used to identify the content of images. However, the retrieving process becomes very challenging due to the hard management of large databases in terms of storage, computation complexity, temporal performance and similarity representation. In this paper, we propose a cloud-based platform in which we integrate several features extraction algorithms used for content-based image retrieval (CBIR) systems. Moreover, we propose an efficient combination of SIFT and SURF descriptors that allowed to extract and match image features and hence improve the process of image retrieval. The proposed algorithms have been implemented on the CPU and also adapted to fully exploit the power of GPUs. Our platform is presented with a responsive web solution that offers for users the possibility to exploit, test and evaluate image retrieval methods. The platform offers to users a simple-to-use access for different algorithms such as SIFT, SURF descriptors without the need to setup the environment or install anything while spending minimal efforts on preprocessing and configuring. On the other hand, our cloud-based CPU and GPU implementations are scalable, which means that they can be used even with large database of multimedia documents. The obtained results showed: 1. Precision improvement in terms of recall and precision; 2. Performance improvement in terms of computation time as a result of exploiting GPUs in parallel; 3. Reduction of energy consumption.<\/jats:p>","DOI":"10.3390\/computers8020048","type":"journal-article","created":{"date-parts":[[2019,6,14]],"date-time":"2019-06-14T11:19:58Z","timestamp":1560511198000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Cloud-Based Image Retrieval Using GPU Platforms"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1530-9524","authenticated-orcid":false,"given":"Sidi Ahmed","family":"Mahmoudi","sequence":"first","affiliation":[{"name":"Department of Computer Science, Faculty of Engineering, University of Mons, 7000 Mons, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed Amin","family":"Belarbi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Engineering, University of Mons, 7000 Mons, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2946-854X","authenticated-orcid":false,"given":"El Wardani","family":"Dadi","sequence":"additional","affiliation":[{"name":"LaRi Laboratory, National School of Applied Sciences, Al Hoceima, University of Mohammed First, Oujda 60000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8272-9425","authenticated-orcid":false,"given":"Sa\u00efd","family":"Mahmoudi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Engineering, University of Mons, 7000 Mons, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Benjelloun","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Engineering, University of Mons, 7000 Mons, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,14]]},"reference":[{"key":"ref_1","first-page":"107","article-title":"Invariant feature descriptor based on harmonic image transform for plant leaf retrieval","volume":"25","author":"Zahra","year":"2017","journal-title":"Pertanika J. Sci. Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive Image Features from Scale-Invariant Keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_3","unstructured":"Leonardis, A., Bischof, H., and Pinz, A. (2006). SURF: Speeded Up Robust Features. Computer Vision\u2014ECCV 2006, Proceedings of the 9th European Conference on Computer Vision, Graz, Austria, 7\u201313 May 2006, Part I, Springer."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kusamura, Y., Kozawa, Y., Amagasa, T., and Kitagawa, H. (2016, January 7\u20139). GPU Acceleration of Content-Based Image Retrieval Based on SIFT Descriptors. Proceedings of the 2016 19th International Conference on Network-Based Information Systems (NBiS), Ostrava, Czech Republic.","DOI":"10.1109\/NBiS.2016.55"},{"key":"ref_5","first-page":"1183","article-title":"Traitements d\u2019Images sur Architectures Parall\u00e8les et H\u00e9t\u00e9rog\u00e8nes","volume":"31","author":"Mahmoudi","year":"2012","journal-title":"Tech. Sci. Inform."},{"key":"ref_6","unstructured":"Campilho, A., and Kamel, M. (2014). A Portable Multi-CPU\/ Multi-GPU Based Vertebra Localization in Sagittal MR Images. Image Analysis and Recognition, Springer."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"45","DOI":"10.4018\/IJACI.2017100104","article-title":"PCA as Dimensionality Reduction for Large-Scale Image Retrieval Systems","volume":"8","author":"Belarbi","year":"2017","journal-title":"Int. J. Ambient. Comput. Intell."},{"key":"ref_8","first-page":"2","article-title":"Docker: Lightweight Linux containers for consistent development and deployment","volume":"2014","author":"Merkel","year":"2014","journal-title":"Linux J."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Mahmoudi, S.A., and Manneback, P. (2014, January 14\u201316). Multi-GPU based event detection and localization using high definition videos. Proceedings of the 2014 International Conference on Multimedia Computing and Systems (ICMCS), Marrakech, Morocco.","DOI":"10.1109\/ICMCS.2014.6911183"},{"key":"ref_10","unstructured":"Yang, M., Kpalma, K., and Ronsin, J. (2008). A Survey of Shape Feature Extraction Techniques. Pattern Recognition Techniques, Technology and Applications, IN-TECH."},{"key":"ref_11","unstructured":"Roy, S., Sangineto, E., Demir, B., and Sebe, N. (2019). Metric-Learning based Deep Hashing Network for Content Based Retrieval of Remote Sensing Images. arXiv."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tang, X., Zhang, X., Liu, F., and Jiao, L. (2018). Unsupervised Deep Feature Learning for Remote Sensing Image Retrieval. Remote Sens., 10.","DOI":"10.3390\/rs10081243"},{"key":"ref_13","unstructured":"Wu, C. (2019, June 12). SiftGPU: A GPU Implementation of Scale Invariant Feature Transform SIFT. Available online: https:\/\/github.com\/pitzer\/SiftGPU."},{"key":"ref_14","first-page":"355","article-title":"GPU Accelerating Speeded-Up Robust Features","volume":"8","author":"Terriberry","year":"2009","journal-title":"Int. J. Parallel Program."},{"key":"ref_15","first-page":"1","article-title":"Comprehensive Survey on Distance\/Similarity Measures between Probability Density Functions","volume":"1","author":"Cha","year":"2007","journal-title":"City"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1824","DOI":"10.1109\/JSTARS.2017.2664119","article-title":"SAR Image Content Retrieval Based on Fuzzy Similarity and Relevance Feedback","volume":"10","author":"Tang","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1007\/s00138-013-0501-5","article-title":"CM-BOF: Visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features","volume":"24","author":"Lian","year":"2013","journal-title":"J. Mach. Vis. Appl."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Belarbi, M.A., Mahmoudi, S., Belalem, G., and Mahmoudi, S.A. (2017, January 24\u201326). Web-based Multimedia Research and Indexation for Big Data Databases. Proceedings of the 3rd International Conference on Cloud Computing Technologies and Applications\u2014CloudTech\u201917, Rabat, Morocco.","DOI":"10.1109\/CloudTech.2017.8284719"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Benjelloun, M., Dadi, E.W., and Daoudi, E.M. (2018). GPU-based Acceleration of Methods based on Clock Matching Metric for Large Scale 3D Shape Retrieval. Scalable Comput., 19.","DOI":"10.12694\/scpe.v19i1.1391"},{"key":"ref_20","unstructured":"Belarbi, M.A., Mahmoudi, S.A., Mahmoudi, S., and Belalem, G. (2019). A New Parallel and Distributed Approach for Large Scale Images Retrieval. Cloud Computing and Big Data: Technologies, Applications and Security, Springer."},{"key":"ref_21","unstructured":"Benjelloun, M., Dadi, E.W., and Daoudi, E.M. (2016). 3D shape retrieval in distributed databases. Int. J. Imaging Robot., 16."},{"key":"ref_22","unstructured":"Calasanz, R.B.I. (2017, January 17\u201318). Towards the Scientific Cloud Workflow Architecture. Proceedings of the 5th International Workshop on ADVANCEs in ICT Infraestructures and Services (ADVANCE\u20192017), Paris, France."},{"key":"ref_23","unstructured":"Hua, G., and Hua, X.S. (2015). CloudCV: Large-Scale Distributed Computer Vision as a Cloud Service. Mobile Cloud Visual Media Computing: From Interaction to Service, Springer."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1016\/j.procs.2011.04.075","article-title":"The IPOL Initiative: Publishing and Testing Algorithms on Line for Reproducible Research in Image Processing","volume":"4","author":"Limare","year":"2011","journal-title":"Procedia Comput. Sci."},{"key":"ref_25","unstructured":"Yan, Y., and Huang, L. (2014). Large-Scale Image Processing Research Cloud. Cloud Comput., 88\u201393."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"e4372","DOI":"10.1002\/cpe.4372","article-title":"Towards a smart selection of resources in the cloud for low-energy multimedia processing","volume":"30","author":"Mahmoudi","year":"2018","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2","DOI":"10.7559\/citarj.v10i2.494","article-title":"Real Time Web-based Toolbox for Computer Vision","volume":"10","author":"Mahmoudi","year":"2018","journal-title":"J. Sci. Technol. Arts"},{"key":"ref_28","unstructured":"Udit, G. (2015). Comparison between security majors in virtual machine and linux containers. arXiv."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Liu, X., Feng, C., Yuan, D., and Wang, C. (2010, January 28\u201330). Design of secure FTP system. Proceedings of the 2010 International Conference on Communications, Circuits and Systems (ICCCAS), Chengdu, China.","DOI":"10.1109\/ICCCAS.2010.5582002"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Alshammari, R.H. (2007, January 7\u201310). A flow based approach for SSH traffic detection. Proceedings of the 2007 IEEE International Conference on Systems, Man and Cybernetics (ISIC), Montreal, QC, Canada.","DOI":"10.1109\/ICSMC.2007.4414006"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1145\/228503.228509","article-title":"Securing the commercial Internet","volume":"39","author":"Bhimani","year":"1996","journal-title":"Commun. ACM"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/MSP.2009.12","article-title":"Man-in-the-Middle Attack to the HTTPS Protocol","volume":"7","author":"Bhimani","year":"2009","journal-title":"IEEE Secur. Priv."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Dudani, S.A. (1976). The distance-weighted k-nearest-neighbor rule. IEEE Trans. Syst. Man Cybern., 325\u2013327.","DOI":"10.1109\/TSMC.1976.5408784"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Mahmoudi, S.A., and Manneback, P. (2015). Multi-CPU\/Multi-GPU Based Framework for Multimedia Processing. Computer Science and Its Applications, Springer.","DOI":"10.1007\/978-3-319-19578-0_5"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Mahmoudi, S.A., and Manneback, P. (2012, January 15\u201318). Efficient exploitation of heterogeneous platforms for images features extraction. Proceedings of the 2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA), Istanbul, Turkey.","DOI":"10.1109\/IPTA.2012.6469569"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.cviu.2013.10.007","article-title":"Detecting, segmenting and tracking unknown objects using multi-label MRF inference","volume":"118","author":"Kragic","year":"2014","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_37","unstructured":"Paleo, P. (2019, June 12). An Implementation of SIFT on GPU with OpenCL. Available online: https:\/\/github.com\/pierrepaleo\/sift_pyocl."}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/8\/2\/48\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:58:29Z","timestamp":1760187509000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/8\/2\/48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,14]]},"references-count":37,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,6]]}},"alternative-id":["computers8020048"],"URL":"https:\/\/doi.org\/10.3390\/computers8020048","relation":{},"ISSN":["2073-431X"],"issn-type":[{"value":"2073-431X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6,14]]}}}