|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Enhancing Privacy and Accuracy in Outsourced SIFT: Efficient Image Feature Extraction |
| Authors Name: | Jai Suriya S , David Prakash M , Krishna Kumar G , Ramanan K |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_219936
|
| Published Paper Id: | IJNRD2404751 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | The advent of cloud computing has spurred the demand for secure and efficient picture recovery methods. This paper proposes a novel technique that harnesses the power of cloud infrastructure while prioritizing data security and retrieval accuracy. Central to the approach is the utilization of the Scale Invariant Feature Transformation (SIFT) algorithm for robust feature extraction from images. These features, encapsulating distinctive local image structures, serve as the basis for subsequent retrieval operations. Upon extraction, the system computes the Manhattan distances between the query images SIFT descriptors and those of images stored within the cloud database. This distance metric, known for its effectiveness in feature matching tasks, facilitates the identification of candidate images that closely resemble the query. To optimize retrieval efficiency, a balancing index tree structure is employed for organizing and storing the feature descriptors of images. This ensures rapid search operations, even in scenarios with a vast repository of images. Furthermore, stringent measures are implemented to safeguard data integrity and confidentiality. Before storage in the cloud, images and associated index are stored securely, mitigating risks associated with unauthorized access. The proposed technique offers a comprehensive solution for secure and efficient picture recovery in cloud environments. By integrating advanced image processing algorithms, efficient data structures, and robust encryption mechanisms, the system provides users with a reliable means to retrieve relevant images while safeguarding sensitive information. |
| Keywords: | Convolutional Neural Networks (CNNs), Scale Invariant Feature Transformation (SIFT), Class Similarity Network (CSN) |
| Cite Article: | "Enhancing Privacy and Accuracy in Outsourced SIFT: Efficient Image Feature Extraction", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h431-h437, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404751.pdf |
| Downloads: | 00020 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2404751 Registration ID: 219936 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: h431-h437 Country: Salem, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404751 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404751 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn