In the modern age of computing and technology, computer vision has become a key aspect of numerous innovations and solutions that make everyday life easier. Object recognition in images is one area where computer vision can contribute to significant improvements. Playing chess, one of the oldest and most challenging intellectual games requires concentration and tactical thinking. In computer vision, automating the recognition of chessboards and figures can contribute to developing advanced chess applications, help users analyse games, or even enable a game with a computer based on real-world chess setups. This paper describes how the system for recognising chessboards and figures using computer vision techniques was developed and implemented. Through analysing existing methods, designing a new algorithm, and experimental evaluation, the goal is to create an accurate and efficient system that can recognise chess positions and individual figures based on images.