Emergency Vehicle Recognition and Classification Method Using HSV Color Segmentation

Classification and recognition of emergency vehicles in traffic surveillance cameras offer an early warning to ensure the prompt reaction to the traffic about emergency stating. Much existing traffic surveillance camera detection monitoring based on computer vision technology has achieved high detection rates. Some of them are very innovative and have a higher novelty index. One of the innovative ideas is detecting an emergency vehicle in the moving traffic routes from the input of a video surveillance camera. The Classification and recognition of emergency vehicles in traffic surveillance cameras offer an early warning to ensure the prompt reaction to the traffic about emergency stating. This paper proposes an algorithm which addresses a novel visual analysis technique for Detecting a moving emergency vehicle in traffic surveillance camera using a combination of Hue Saturation and Value (HSV) color segmentation and support vector machine (SVM). Experiments conducted on various benchmarking databases show that the proposed algorithm successfully distinguishes the emergency vehicles from the traffic in a surveillance camera. The results show that the proposed algorithm has an innovative classification method, a higher accuracy rate, as well as comparable recall and specificity, compared with other methods.