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DOI: 10.14569/IJACSA.2022.0131116
PDF

Object Pre-processing using Motion Stabilization and Key Frame Extraction with Machine Learning Techniques

Author 1: Kande Archana
Author 2: V Kamakshi Prasad

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 11, 2022.

  • Abstract and Keywords
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Abstract: Video information processing is one of the most important application areas in research and to solve in various pre-processing issues. The pre-processing issues such as unstable video frame rates or capture angle, noisy data and large size of the video data prevent the researchers to apply information retrieval or categorization algorithms. The video data itself plays a vital role in various areas. This work aims to solve the motion stabilization, noise reduction and key frame extraction, without losing the information and in reduced time. The work results into 66% reduction in key frame extraction and nearly 6 ns time for complete video data processing.

Keywords: Information loss preventive; mean angle measure; key frame extraction; moving average; dynamic thresholding

Kande Archana and V Kamakshi Prasad, “Object Pre-processing using Motion Stabilization and Key Frame Extraction with Machine Learning Techniques” International Journal of Advanced Computer Science and Applications(IJACSA), 13(11), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131116

@article{Archana2022,
title = {Object Pre-processing using Motion Stabilization and Key Frame Extraction with Machine Learning Techniques},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131116},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131116},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {11},
author = {Kande Archana and V Kamakshi Prasad}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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