Many modern information processing and control systems for various fields are based on software and hardware for image processing and analysis. At the same time, it is often necessary to ensure the storage and transmission of large data sets, including image collections. Data compression technologies are used to reduce the amount of memory required and increase the speed of information transmission. To date, approaches based on the use of discrete wavelet transformations have been developed and applied. The advantage of these transformations is the ability to localize the points of brightness change in images. The detailing coefficients corresponding to such points make a significant contribution to the energy of the image. This contribution can be quantified in the form of weights, the analysis of which allows us to determine the method of quantization of the coefficients of the wavelet transform in the proposed lossy compression method. The approach described in the paper corresponds to the general scheme of image compression and provides for the stages of transformation, quantization and encoding. It provides good compression performance and can be used in information processing and control systems.

Keywords: image processing, image compression, redundancy in images, general image compression scheme, wavelet transform, compression based on wavelet transform, weight model, significance of detail coefficients, quantization, entropy coding

Currently, there is an increase in the number of scientific papers on models, methods and software and hardware for image processing and analysis. This is due to the widespread introduction of computer vision technologies into information processing and control systems. At the same time, approaches that provide fast image processing in real time using limited computing resources are relevant. Such approaches are usually based on low-level image filtering algorithms. One of the tasks to be solved in computer vision-based systems is the localization of round objects. These objects have the property of radial symmetry. Therefore, the approach based on the Fast Radial Symmetry Transform, which is considered in this paper, is effective for solving this problem. The paper describes the basic steps of the basic transformation, provides a procedure for determining the centers of radially symmetric areas for localization of round objects in images, and discusses examples of its application.

Keywords: computer vision, image processing, image analysis, localization of objects, methods of localization of round objects, fast radial symmetry transf, detecion of the centers of radially symmetric areas