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THE ONTOLOGY-BASED METHODOLOGY FOR DETERMINING THE OBJECTS- GEOMETRIC PARAMETERS FROM PRE-PROCESSED DIGITAL IMAGES FOR APPLIED PHOTOGRAMMETRY
Abstract
One of the main processes of functioning of digital measuring systems is image analysis. For photogrammetric systems, such tasks involve searching, counting the number of objects of a given type, followed by determining their geometric characteristics. The main problem that impedes the direct application of methods is the provision of a given level of measurement error. Methods, depending on their specific combinations and input parameters, can give different results. This is due both to the quality of the image itself and to the placement of the measured objects on the scene. In order to reduce the negative impact of this problem and ensure the predicted value of the total measurement error, it is necessary to be able to know before the start of the procedure a combination of methods and their parameters that will give the best result in terms of the ratio of quality and computational costs. One of the ways to provide this opportunity is knowledge of the applicability of methods and their combinations for individual tasks. For this purpose, the procedures of inductive training of photogrammetric algorithms based on observation of the operator?s actions in the manual measurement mode were previously developed. Based on these procedures, an ontology of photogrammetric methods and their combinations was formed, as well as tools for its automated extension. The ontology is described in the OWL language and is hosted in a cloud environment, which ensures its continuous availability. The article proposes the above ontological model, as well as a method for determining the geometric parameters of objects based on it.
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