Our project idea came from a group of students at the Technion with visual impairment. They described a problem where blind people have great difficulty to pass safely pedestrian crossings. A possible solution to this problem is to use a smartphone to take images of the pedestrian crossing area and then, using a sophisticated image processing algorithm, to get an output whether it is safe to pass the pedestrian crossing.
Our main target of this project was to implement an algorithm which will receive as input a color image and his output will be the information if there is a traffic light, in case that there will be a traffic light the algorithm would identify if the traffic light is green or red.
In this project, we investigated and implemented such an algorithm using MATLAB. We implemented the algorithm with machine learning boosting methods. To train our system, we have created a database of images that contain about 300 pedestrian traffic lights. We tested our algorithm with image from the database in a leave-one-out approach.
After improving our algorithm we got the next results:
81% for identifying green traffic light.
92% for identifying red traffic light.