Modeling of reasoning when searching for objects in images

Abstract

Visual patterns, for example, handwritten letters or objects of aerospace observations, are highly variable. The high variety and large volume of unstructured information lead to the need for complex and resource-intensive calculations. Unfortunately, image analysis approaches based on the domain ontology do not specify any method for automatic selection of criteria (features) and decision-making rules. Insufficient structuredness of cases and a large variability of object images lead to a rapid growth of the case base, which significantly reduces the performance of the decision support system. The article proposes an approach to the structural analysis of images, which consists in sequential refinement of objects' features and weakening of interpretation rules during an iterative search of facts using the ontology of images represented as attributed graphs of relationships between elements of objects. The algorithm of reasoning on graphic information consists in the sequence of task (functional) actions necessary for processing and analyzing the image in accordance with the task, the actions of the system to prepare conditions for their implementation, as well as to organize and manage the reasoning process.