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Physical Characterization of Particulate Matter Employing Support Vector Machine Aided Image Processing

Mogireddy, Kranthi Kumar Reddy
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1297358759

Abstract Details

2011, Master of Science in Electrical Engineering, University of Toledo, Electrical Engineering.
A detailed knowledge of particulates released during combustion is vital for managing an air quality program. Comprehending the chemical and physical characteristics of particulates is essential to solve health problems, smog formations, acid rain issues, and climate changes. Over the last 30 years, environmental professionals have started investigating non-destructive techniques to evaluate physical characteristics because of its substantial affects on human health. This thesis presents Scanning Electron Microscope (SEM) integrated with image processing technique as a tool for physical characterization of particulate matter. The characterization process involves image reading, preprocessing, segmentation, feature extraction, and representation steps. In these steps, selection of optimal image segmentation algorithm is the key for analyzing the captured images of fine particulate matter. In this thesis, a novel frame work for automating the process of selecting optimal image segmentation algorithm for each image using Support Vector Machines (SVMs) is presented. In addition to this, an image processing algorithm is developed based on Sobel edge detection method for statistical determination of various morphological parameters including area, diameter and shape factor of the particles.
Vijay Devabhaktuni, PhD (Committee Chair)
Ashok Kumar, PhD (Committee Co-Chair)
Ezzatollah Salari, PhD (Committee Member)
73 p.
Computer Engineering; Electrical Engineering
Particulate Matter; Image Processing; Support Vector Machine; SVM

Recommended Citations

Citations

  • Mogireddy, K. K. R. (2011). Physical Characterization of Particulate Matter Employing Support Vector Machine Aided Image Processing [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1297358759

    APA Style (7th edition)

  • Mogireddy, Kranthi Kumar Reddy. Physical Characterization of Particulate Matter Employing Support Vector Machine Aided Image Processing. 2011. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1297358759.

    MLA Style (8th edition)

  • Mogireddy, Kranthi Kumar Reddy. "Physical Characterization of Particulate Matter Employing Support Vector Machine Aided Image Processing." Master's thesis, University of Toledo, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1297358759

    Chicago Manual of Style (17th edition)

toledo1297358759
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© 2011, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.