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

被引:0
|
作者
Archana, Kande [1 ]
Prasad, V. Kamakshi [1 ]
机构
[1] Jawaharlal Nehru Technol Univ JNTU, Dept CSE, Hyderabad, Telangana, India
关键词
Information loss preventive; mean angle measure; key frame extraction; moving average; dynamic thresholding;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:148 / 157
页数:10
相关论文
共 50 条
  • [31] Detection of Brain Tumour in Medical Images Using Pre-Processing Techniques
    Monika, Surineni
    Malathi, K.
    Monisha, Surineni
    RESEARCH JOURNAL OF PHARMACEUTICAL BIOLOGICAL AND CHEMICAL SCIENCES, 2016, 7 : 78 - 87
  • [32] Brain Tissue Segmentation Using NeuroNet With Different Pre-processing Techniques
    Islam Tushar, Fakrul
    Alyafi, Basel
    Hasan, Kamrul
    Dahal, Laysen
    2019 JOINT 8TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV) AND 2019 3RD INTERNATIONAL CONFERENCE ON IMAGING, VISION & PATTERN RECOGNITION (ICIVPR) WITH INTERNATIONAL CONFERENCE ON ACTIVITY AND BEHAVIOR COMPUTING (ABC), 2019, : 223 - 227
  • [33] Package Proposal for Data Pre-Processing for Machine Learning Applied to Precision Irrigation
    dos Santos, Rogerio Pereira
    Beko, Marko
    Leithardt, Valderi R. Q.
    2023 6TH CONFERENCE ON CLOUD AND INTERNET OF THINGS, CIOT, 2023, : 141 - 148
  • [34] Image Pre-processing and Feature Extraction Techniques for Magnetic Resonance Brain Image Analysis
    Hemanth, D. Jude
    Anitha, J.
    COMPUTER APPLICATIONS FOR COMMUNICATION, NETWORKING, AND DIGITAL CONTENTS, 2012, 350 : 349 - 356
  • [35] Impact of Data Pre-Processing Techniques on Deep Learning Based Power Attacks
    Aljuffri, Abdullah
    Reinbrecht, Cezar
    Hamdioui, Said
    Taouil, Mottaqiallah
    2021 16TH INTERNATIONAL CONFERENCE ON DESIGN & TECHNOLOGY OF INTEGRATED SYSTEMS IN NANOSCALE ERA (DTIS 2021), 2021,
  • [36] FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning
    Khalid, Faiq
    Hanif, Muhammad Abdullah
    Rehman, Semeen
    Qadir, Junaid
    Shafique, Muhammad
    2019 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2019, : 902 - 907
  • [37] Pre-processing satellite rainfall products improves hydrological simulations with machine learning
    Boulmaiz, Tayeb
    Hafsi, Radia
    Guermoui, Mawloud
    Boutaghane, Hamouda
    Abida, Habib
    Saber, Mohamed
    Kantoush, Sameh A.
    Ferkous, Khaled
    Tramblay, Yves
    HYDROLOGICAL SCIENCES JOURNAL, 2024, 69 (10) : 1356 - 1370
  • [38] A Multi-purpose Data Pre-processing Framework using Machine Learning for Enterprise Data Models
    Ramana, Venkata B.
    Narsimha, G.
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2021, 12 (03) : 646 - 656
  • [39] Classification of Astronomical Objects in the Galaxy M81 using Machine Learning Techniques II. An Application of Clustering in Data Pre-processing
    Chuntama, Tapanapong
    Suwannajak, Chutipong
    Techa-Angkoon, Prapaporn
    Panyangam, Benjamas
    Tanakul, Nahathai
    2021 18TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE-2021), 2021,
  • [40] Insights into enhanced machine learning techniques for surface water quantity and quality prediction based on data pre-processing algorithms
    Panahi, Javad
    Mastouri, Reza
    Shabanlou, Saeid
    JOURNAL OF HYDROINFORMATICS, 2022, : 875 - 897