Descriptive Image Analysis

Abstract

An overview of the main methods, models, and results of Descriptive Image Analysis is given. Descriptive Image Analysis is a logically organized set of descriptive methods and models designed for image analysis and evaluation. The state of the art and trends in the development of Descriptive Image Analysis are determined by the methods, models, and results of the Descriptive Approach to image analysis and understanding. As the methods and apparatus of the Descriptive Approach to the analysis and understanding of images were developed and refined, its interpretation was proposed, defined as Descriptive Image Analysis. The main goal of Descriptive Image Analysis is to structure and standardize the various methods, processes, and concepts used in image analysis and recognition. Descriptive Image Analysis solves the fundamental problems of formalizing and systematizing methods and forms of information representation in image analysis, recognition, and understanding problems, in particular, associated with automating the extraction of information from images to make intelligent decisions (diagnosis, prediction, detection, assessment, and identification patterns of objects, events and processes). Descriptive Image Analysis makes it possible to solve both problems related to constructing formal descriptions of images as recognition objects and problems of synthesizing procedures for recognizing and understanding images. It is suggested that the processes of analysis and evaluation of information represented in the form of images (problem solution trajectories) can generally be considered a sequence/combination of transformations and calculations of a set of intermediate and final (determining the solution) estimates. These transformations are defined by equivalence classes of images and their representations. The latter are defined descriptively, i.e., using a basic set of prototypes and corresponding generating transformations that are functionally complete with respect to the equivalence class of admissible transformations. As part of Descriptive Image Analysis, the following main results were obtained: (1) new mathematical objects were introduced and studied: image formalization space, descriptive image algebras, descriptive algorithmic schemes; (2) descriptive image analysis models have been defined and studied: image models, image transformation models, models for generating descriptive algorithmic schemes; (3) linguistic and knowledge-oriented tools have been developed to support the automation of image analysis; (4) a number of automated software systems have been developed and axioms for Descriptive Image Analysis proposed. A general description of the provisions of Descriptive Image Analysis is presented, and the main results of research in the first two directions are discussed: new mathematical objects and image analysis models. A comprehensive bibliography on Descriptive Image Analysis is provided.