HYBRID ALGORITHM OF AUTOMATIC TRACKING FOR EMBEDDED COMPUTERS OF OPTOELECTRONIC NAVIGATION AND GUIDANCE SYSTEMS

Abstract

The authors of the work carried out research in the field of technical vision systems, as well as approaches to solving problems of detecting and tracking objects of interest without a priori knowledge of their type, taking into account the target platform in the form of an embedded optoelectronic system computer. Based on the data obtained, the sphere was analyzed and a new hybrid maintenance algorithm for embedded systems was proposed. It is based on a combination of several types of maintenance algorithms, with one of them as a priority, providing the main work, and several auxiliary ones to stabilize and expand the functionality of the priority one. They are connected by an external processing cycle, which, based on a consensus decision of internal algorithms, independently decides on the position of the target object in the frame and stores auxiliary information to ensure the correct operation of the entire algorithm, as well as responsible for making a decision on the re-detection of the target. The authors propose two possible implementations of this approach, used depending on the power of available computing resources. A variant of the algorithm has been implemented for the available computing power, and its semi-natural tests have been carried out based on real video sequences. They represent different backgrounds and different structural objects of interest with different dynamics of change over time. The evaluation of the results of the proposed algorithm in the tasks of detecting and tracking an object of interest in real time on the presented videos using a software package for automating testing of detection and tracking algorithms has been carried out. As a result, the algorithm showed high efficiency in the tasks set, improving the accuracy of tracking, in comparison with internal algorithms that worked separately, by adding rotary and scale invariances, and also significantly increased the ability to re-detect an object after its loss. In conclusion, the authors present proposals for the further development and implementation of optoelectronic systems into embedded computers