Authors:
Elio D. Di Claudio
;
Giovanni Jacovitti
;
Gianni Orlandi
and
Andrea Proietti
Affiliation:
University of Rome "La Sapienza", Italy
Keyword(s):
Dust Monitoring, Object Classification, Contour Analysis.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Classification
;
Computer Vision, Visualization and Computer Graphics
;
Feature Selection and Extraction
;
Image Understanding
;
Object Recognition
;
Pattern Recognition
;
Shape Representation
;
Software Engineering
;
Theory and Methods
Abstract:
A fast and versatile method for classifying dust particles dispersed in the air is presented. The method uses
images captured by a simple imaging system composed of a photographic sensor array and of an illuminating
source. Such a device is exposed to free particulate deposition from the environment, and its accumulation is
measured by observing the shadows of the particles the air casts onto the photographic sensor. Particles are
detected and classified in order to measure their density and to analyse their composition. To this purpose,
the contour paths of particle shadows are traced. Then, distinctive features of single particles, such as dimension
and morphology, are extracted by looking at corresponding features of the sequence of local orientation
changes of contours. Discrimination between dust and fibre particles is efficiently done using the varimax
norm of these orientation changes. It is shown through field examples that such a technique is very well suited
for quantitativ
e and qualitative dust analysis in real environments.
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