DETECTION OF TRAFFIC SIGNALS USING COLOR SEGMENTATION AND A RADIAL SYMMETRY DETECTOR
Currently, unmanned systems for controlling various vehicles, including cars, are becoming widespread. Driving an unmanned vehicle involves solving problems related to the recognition of traffic objects: pedestrians, cars, obstacles (in the form of holes, bumps, poles, trees, buildings, etc.), road signs, markings, traffic lights. An algorithm for solving the problem of detecting and recognizing circular traffic signals is proposed. To solve this problem, the following are involved: rapid transformation of radial symmetry, color segmentation, morphological operations. A feature of the algorithm is that the areas of the location of the light signals are preliminarily determined by color, followed by the refinement of the shape and position of objects in the image. Based on the proposed method, software was developed for detecting traffic signals in photographs. The software was tested on a publicly available database of images containing traffic lights. The proposed algorithm has shown its efficiency, it can be expanded in terms of the types of signals recognized and used as part of control systems for unmanned vehicles, as well as part of driver assistance systems for solving problems to prevent dangerous and emergency situations