Object detection algorithms application to the problem of recognizing the level of blood in a test tube for biosamples aliquoting

This work is devoted to the analysis of the application of object detection algorithms for recognizing the level of blood in a test tube. Based on the initial data and data received from the sensory system, pattern recognition is performed and decisions are made to complete the task. It is necessary to control the level of the liquid being determined in the test tube to solve the technological problems of biomaterial aliquoting. In this case, it should be taken into account that the liquid has two fractions that differ in color: a blood clot and serum. The glare of the tube surface and lighting features should also be taken into account. These factors greatly complicate the operation of the vision system. Software in Python language have been developed that implement the ability of a vision system to recognize the level of blood in test tubes and visualize the recognized blood level in several ways: contour selection, dot marking, color filtering. The developed methods are supposed to be applied for biosamples aliquoting using a delta robot in a multirobotic system, which will increase the productivity of ongoing biomedical research through the application of new technical solutions and principles of intelligent robotics. Visualized results of the work of the programs under consideration are presented and an assessment of the quality of recognition implementation is given.