The paper is devoted to the search for new approaches to encrypting selected objects in an image. Videos were analyzed, which were divided into frames, and in each video frame, the necessary objects were detected for further encryption. Images of objects with a designated geometric shape and color characteristics of pixels were considered. To select objects, a method was used based on the calculation of average values, the analysis of which made it possible to determine the convergence with the established image. Dividing the selected field into subregions with different shapes solves the problem of finding objects of the same type with different scales. In addition, the paper considers the detection of moving objects. The detection of moving objects is carried out based on determining the frame difference in pixel codes in the form of a rectangular shape. Cellular automata technology was used for encryption. The best results were shown by the transition rules of elementary cellular automata, such as: 90, 105, 150, and XOR function. The use of cellular automata technologies made it possible to use one key sequence to encrypt objects on all video frames of the video. Encryption results are different for the same objects located in different places of the same video frame and different video frames of the video sequence. The video frame image is divided into bit layers, the number of which is determined by the length of the code of each pixel. Each bit layer is encrypted with the same evolution, which is formed by one initial key bit sequence. For each video frame, a different part of the evolution is used, as well as for each detected object in the image. This approach gives different results for any objects that have a different location both on the video frame image and in different video frames. The described methods allow you to automate the process of detecting objects on video and encrypting them.