One Approach to intellectual image analysis

Abstract

Abstract. This study investigated the method of semantic image analysis by using a set of neuron-like detectors of foreground objects. This method is intended to find different types of foreground objects and to determine properties of these objects. As a result of semantic analysis the semantic descriptor of the image is created. The descriptor is a set of foreground objects of the image and a set of properties for each object. The distance between images is defined as distance between their semantic descriptors. Using the concept of distance between images, "semantically similarity" between images or videos is defined.

A Biomorphic Model of Cortical Column for Content—Based Image Retrieval

“…Since the learning process of the detector is visualized, one can trace the formation of a column detector of specific stimuli: face, figure, number, etc. Thus, in the course of the development of a hierarchical system for semantic image analysis based on multistage detection, there occurs a metamorphosis: it appears that the technical system [1, [56][57][58] can be considered a biomorphic model of structural and functional modules for information processing in living systems.…”

“…An intelligent artificial cognitive system was developed back in 2015 [1]. This system performs intellectual image analysis in accordance with a given semantic dictionary (for example, recognition of symbolic information) [56][57][58]. In the course of the development of an artificial cognitive system for content-based image analysis, a biomorphic model for the construction and interaction of structural and functional modules of living systems during visual signal processing was constructed.…”