A vision based system for traffic lights recognition
In this article a traffic light recognition with status detection system is introduced. The system is evaluated from a generic point of view but the applications range from Intelligent Transportation System (ITS) to visual impaired and color vision deficiencies aid to safely cross streets. The algorithm is based on color segmentation in HSV color space. After that candidates reduction is performed using a pipeline approach to speed up the algorithm. Resulting candidates are input to feature extraction and support vector machine is then applied. For the training of the Support Vector Machine a database with images collected in Chicago is used. Unlike other works the purpose is to evaluate different performance according to the feature extraction. In particular HOG, HAAR and LBP features are compared. The purpose is also to create a database to be used from other researchers. The result is accurate and reliable provided that good quality images are input to the system.