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

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

Physical Characterization of Particulate Matter Employing Support Vector Machine Aided Image Processing PDF Author: Kranthi Kumar Reddy Mogireddy
Publisher:
ISBN:
Category : Computer algorithms
Languages : en
Pages : 61

Book Description
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.
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