Elements marking of partially masked group objects using local descriptions of an associated continuous image

Questions of recognizing images of multiple objects whose dimensions are close to the resolution limit of recording equipment - groups of point objects (GPO) - are investigated. Images in the form of GPOs are found in radar images, whereas images of large-scale objects represented by characteristic points, clusters of data in a feature space, and events in mass service systems and automated control systems can be reduced to them. GPO recognition is complicated by disconnectedness of constituent elements, the narrowness of the image autocorrelation function in terms of the geometric transform parameters, spatial fluctuations of elements, false markings and omissions of signal markings. The most promising approaches to the image recognition of this type are based on the transformation of the GPO into a connected object - an associated continuous image (ACI) - and the analysis of its secondary features. However, for GPO with a non-stationary configuration and / or partially masked GPO, the recognition issues are still poorly investigated. The paper proposes an approach to the recognition of GPO based on the marking of their elements - the identification of point objects to within a metaclass (family, type) that is stable for nonstationary and partially masked GPOs. Four metaclasses are proposed: the extreme and inner points of the GPO with a chain structure, the outer and inner points of clusters. The essence of the approach to marking point marks is the recognition of complex-valued contour codes composed of samples of the cylindrical sections of an associated continuous image (ASI) around the GPO elements. To form the ASI, a vector field with partial sources in the elements of the GPO is used. Evaluations of the reliability of marking under various observation conditions are obtained. The results of marking are both of independent significance for various applied problems and suited for the subsequent recognition of GPO. Approaches to GPO recognition based on the results of marking of their elements are suggested.