A Survey On Image and video Metadata using AI and Image Processing

Authors

  • Prof. Y. L. Tonape  Department of Computer Engineering, S.B. Patil COE, Indapur, Maharashtra, India
  • Gosavi Kiran  Department of Computer Engineering, S.B. Patil COE, Indapur, Maharashtra, India
  • Jagdale Shubham  Department of Computer Engineering, S.B. Patil COE, Indapur, Maharashtra, India
  • Kumbhar Aniket  Department of Computer Engineering, S.B. Patil COE, Indapur, Maharashtra, India
  • Mane Rohit  Department of Computer Engineering, S.B. Patil COE, Indapur, Maharashtra, India

Keywords:

Artificial Intelligence, Image Processing, Video Analysis, Feature and data Extraction, Metadata Object Detection.

Abstract

Automatic Metadata extraction and generation in the context of e-learning standards is usually referred to algorithms able to process semi structured documents in plain text. As most of the information available on the web nowadays is unstructured and in the form of multimedia files, the need for more general approaches arises. We propose an automatic metadata generation procedure that allows to label specific unstructured data (video lectures) with metadata compliant to the SCORM reference model. After pre-processing, three different summarization algorithms are tested and used to obtain a synthetic description of video content, both in terms of Description and Title. Results show that, in the provided context, the Description field of videos has a good agreement with the true lesson abstract written by a human expert.

References

  1. Spencer A. Thomas1 “Combining Image Features and Patient Metadata to Enhance Transfer Learning” arXiv:2110.05239v1 [cs.CV] 8 Oct 2021
  2. Joel Pepper, Jane Greenberg, Yasin Bakis, etc. “Automatic Metadata Generation for Fish Specimen Image Collections” bioRxiv preprint doi: https://doi.org/10.1101/2021.10.04.463070; this version posted October 5, 2021.
  3. Antonio Maratea, Alfredo Petrosino, Mario Manzo “Generation of Description Metadata for Video Files” June 2013 : https://www.researchgate.net/publication/262270396
  4. Gaikwad, Yogesh J. "A Review on Self Learning based Methods for Real World Single Image Super Resolution." (2021).
  5. V. Khetani, Y. Gandhi and R. R. Patil, "A Study on Different Sign Language Recognition Techniques," 2021 International Conference on Computing, Communication and Green Engineering (CCGE), Pune, India, 2021, pp. 1-4, doi: 10.1109/CCGE50943.2021.9776399.
  6. Vaddadi, S., Arnepalli, P. R., Thatikonda, R., & Padthe, A. (2022). Effective malware detection approach based on deep learning in Cyber-Physical Systems. International Journal of Computer Science and Information Technology, 14(6), 01-12.
  7. Thatikonda, R., Vaddadi, S.A., Arnepalli, P.R.R. et al. Securing biomedical databases based on fuzzy method through blockchain technology. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08355-x
  8. Rashmi, R. Patil, et al. "Rdpc: Secure cloud storage with deduplication technique." 2020 fourth international conference on I-SMAC (IoT in social, mobile, analytics and cloud)(I-SMAC). IEEE, 2020.
  9. Khetani, V., Gandhi, Y., Bhattacharya, S., Ajani, S. N., & Limkar, S. (2023). Cross-Domain Analysis of ML and DL: Evaluating their Impact in Diverse Domains. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 253-262.
  10. Khetani, V., Nicholas, J., Bongirwar, A., & Yeole, A. (2014). Securing web accounts using graphical password authentication through watermarking. International Journal of Computer Trends and Technology, 9(6), 269-274.
  11. Kale, R., Shirkande, S. T., Pawar, R., Chitre, A., Deokate, S. T., Rajput, S. D., & Kumar, J. R. R. (2023). CR System with Efficient Spectrum Sensing and Optimized Handoff Latency to Get Best Quality of Service. International Journal of Intelligent Systems and Applications in Engineering, 11(10s), 829-839.
  12. Nagtilak, S., Rai, S., & Kale, R. (2020). Internet of things: A survey on distributed attack detection using deep learning approach. In Proceeding of International Conference on Computational Science and Applications: ICCSA 2019 (pp. 157-165). Springer Singapore.
  13. Mane, Deepak, and Aniket Hirve. "Study of various approaches in machine translation for Sanskrit language." International Journal of Advancements in Research & Technology 2.4 (2013): 383.
  14. Shivadekar, S., Kataria, B., Limkar, S. et al. Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process. Soft Comput (2023). https://doi.org/10.1007/s00500-023-08709-5
  15. Shivadekar, Samit, et al. "Deep Learning Based Image Classification of Lungs Radiography for Detecting COVID-19 using a Deep CNN and ResNet 50." International Journal of Intelligent Systems and Applications in Engineering 11.1s (2023): 241-250.
  16. Sung Jung Yong , Hyo Gyeong Park , Yeon Hwi You , etc. “Automatic Generation of Video Metadata for the Superpersonalized Recommendation of Media” J. lnf. Commun. Converg. Eng. 20(4): 288-294, Dec. 2022 ISSN: 2234-8255 https://doi.org/10.56977/jicce.2022.20.4.288.
  17. JIAYING LIU1 , XIANGJIE KONG 1 , (Senior Member, IEEE), FENG XIA 1 , etc. “Artificial Intelligence in the 21st Century” July 12, 2018. VOLUME 6, 2018 34403 Digital Object Identifier 10.1109/ACCESS.2018.2819688
  18. Vinoth Kumar Venkatesan 1 , Mahesh Thyluru Ramakrishna 2,*, Anatoliy Batyuk 3 , etc. “High-Performance Artificial Intelligence Recommendation of Quality Research Papers Using Effective Collaborative Approach” Systems 2023, 11, 81. https://doi.org/10.3390/systems11020081
  19. Parlewar, P. ., Jagtap, V. ., Pujeri, U. ., Kulkarni, M. M. S. ., Shirkande, S. T. ., & Tripathi, A. . (2023). An Efficient Low-Loss Data Transmission Model for Noisy Networks. International Journal of Intelligent Systems and Applications in Engineering, 11(9s), 267–276

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-10-30

Issue

Volume 9, Issue 10, September-October-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prof. Y. L. Tonape, Gosavi Kiran, Jagdale Shubham, Kumbhar Aniket, Mane Rohit, " A Survey On Image and video Metadata using AI and Image Processing" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 10, pp.153-157, September-October-2023.