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Image correlation method to simulate physical characteristic of particulate matter

Author

Listed:
  • Deepak Gaur

    (Amity University)

  • Deepti Mehrotra

    (Amity University)

  • Karan Singh

    (JNU)

Abstract

In the modern era, quality of air impacts a lot on human health and on climate change. This change in trend develops an interest for researchers to work on techniques which deal with the monitoring of air quality. This paper, for the first time, applies digital image correlation method to identify the velocity of particulate matter in digital images. Velocity of flowing particles in the atmosphere is a crucial factor of their physical characteristics as fast moving particles effects lot on human health as well as on environmental change. The unique particulate characterization process involves image analysis, preprocessing, calibration, feature extraction and representation. Among all these phases, feature extraction by the digital image correlation method is the key for precisely measuring the velocity of particulate matter present in digital images. Simulated model was found to measure accurate flow of particulate matter in various digital images.

Suggested Citation

  • Deepak Gaur & Deepti Mehrotra & Karan Singh, 2020. "Image correlation method to simulate physical characteristic of particulate matter," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 400-410, April.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:2:d:10.1007_s13198-019-00868-9
    DOI: 10.1007/s13198-019-00868-9
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    References listed on IDEAS

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    1. Eric C. Larson & Gary G. Yen, 2010. "Facial Feature Tracking via Evolutionary Multiobjective Optimization," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 1(1), pages 57-71, January.
    2. Nihar Ranjan Nayak & Bikram Keshari Mishra & Amiya Kumar Rath & Sagarika Swain, 2015. "Improving the Efficiency of Color Image Segmentation using an Enhanced Clustering Methodology," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 6(2), pages 50-62, April.
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