Development of a method for detecting traffic flow objects from satellite photographs with high image quality

Abstract

A set of algorithms used to recognize objects in high-quality satellite photographs is described. This method has a unique ability to detect objects whose dimensions in images do not exceed several tens of pixels. In a photograph, each distinctive area of the image is examined to determine the presence of an object of a certain class, and the probability of this presence in the area in question is calculated. Based on the results of image analysis, a conclusion is drawn about the presence and probable location of the object. A detailed explanation is also given of how the algorithms used in the detection process are learned and parameterized. Taking into account the research results, a wide range of processes can be automated, for example, simplifying the collection and analysis of data in numerous analytical systems. The method has enormous potential and can be effectively used in various fields related to image processing and data analysis, in particular, used for effective traffic management, ensuring uniform loading of the transport network at the limit of its capacity, avoiding overloading of vulnerable areas, as well as forecasting the development of the transport situation. It helps speed up the algorithm for detecting vehicles on satellite images, allows you to assess the state of road traffic and the effectiveness of its organization, identify and predict the development of processes affecting the state of road traffic, as well as monitor the field of safety and traffic management.