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Development of Software to Characterize Particulate Matter in Air Pollution (pp.65-92) $100.00
Authors:  (K. Mogireddy, V. Devabhaktuni, A. Kumar, P. Aggarwal, P. Bhattacharya, EECS Department, Univ. of Toledo, Toledo, Ohio, USA, and others)
Abstract:
This chapter presents the Scanning Electron Microscope (SEM) integrated with image
processing technique as a tool for physical characterization of particulate matter. The
characterization process involves steps of image reading, preprocessing, segmentation, feature
extraction, and representation. In these steps, selection of optimal image segmentation
algorithm is the key for analyzing the captured images of fine particulate matter. A review of
popular image analyzing software available for analyzing SEM images is presented. A new
software employing Image processing and Support Vector Machines (SVM) for particle
characterization is presented. SVM use gray level histograms as an image feature to select the
best segmentation algorithm for the particle images. 


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Development of Software to Characterize Particulate Matter in Air Pollution (pp.65-92)