Content based image search in openstack swift
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.
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Brac University
2024
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| Acesso em linha: | http://hdl.handle.net/10361/22060 |
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10361-220602024-01-03T21:02:33Z Content based image search in openstack swift Ali Uday, Mir Rownak Islam Sakif, Md. Sadiqul Mukta, Jannatun Noor Department of Computer Science and Engineering, Brac University Deep learning Convolutional Neural Networks (CNN) OpenStack Cloud computing YoloV4 Darknet Cloud computing This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 41-44). The OpenStack Object Store, also known as Swift, is a cloud storage software. Swift is optimized for durability, availability; also concurrency across the entire data set. However, Swift does not have a proper technique to let users and administrators search inside the object storage without the entire OpenStack Infrastructure. In this paper, we propose a Content-Based Image Model for Swift, which enables us to extract additional information from images and store it into an elasticsearch database which helps us to search for our desired data based on its contents. This novel approach works in 2 parallel stages. First, the image which is being uploaded is sent to our trained model for object detection. Secondly, this information is being sent to the elasticsearch, which in return helps us to do the searching based on the contents of the uploaded images. As the accuracy of the search solely depends on the accuracy of the object detection model, we have trained our model with MS COCO Dataset. Lastly, we upload these images in various segments to find out the efficacy of our model not only in real-life small and medium-size Swift object storages but also as a user-centered Content-based image retrieval system from a text-based database. Mir Rownak Ali Uday Md. Sadiqul Islam Sakif B.Sc. in Computer Science 2024-01-03T08:08:27Z 2024-01-03T08:08:27Z 2021 2021-09 Thesis ID: 17101088 ID: 17301137 http://hdl.handle.net/10361/22060 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 44 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Deep learning Convolutional Neural Networks (CNN) OpenStack Cloud computing YoloV4 Darknet Cloud computing |
| spellingShingle |
Deep learning Convolutional Neural Networks (CNN) OpenStack Cloud computing YoloV4 Darknet Cloud computing Ali Uday, Mir Rownak Islam Sakif, Md. Sadiqul Content based image search in openstack swift |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021. |
| author2 |
Mukta, Jannatun Noor |
| author_facet |
Mukta, Jannatun Noor Ali Uday, Mir Rownak Islam Sakif, Md. Sadiqul |
| format |
Thesis |
| author |
Ali Uday, Mir Rownak Islam Sakif, Md. Sadiqul |
| author_sort |
Ali Uday, Mir Rownak |
| title |
Content based image search in openstack swift |
| title_short |
Content based image search in openstack swift |
| title_full |
Content based image search in openstack swift |
| title_fullStr |
Content based image search in openstack swift |
| title_full_unstemmed |
Content based image search in openstack swift |
| title_sort |
content based image search in openstack swift |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22060 |
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AT aliudaymirrownak contentbasedimagesearchinopenstackswift AT islamsakifmdsadiqul contentbasedimagesearchinopenstackswift |
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