Door detection in images of 3D scenes in an electronic travel aid for the blind

In this paper we propose a fast method for detecting doors in images of 3D scenes. First, the equation estimating the orientation and location of the ground surface is computed. This information is used in further processing steps of the algorithm. Then, the edge image is calculated (using the Canny edge detector) and line segments justifying predefined conditions are searched for by applying the Probabilistic Hough Transform method. Pairs of parallel line segments perpendicular to the ground surface located at a distance range 80–110 cm are identified. The detection performance has been also enhanced by detecting door handles. The proposed method was successfully verified on the recorded indoor RGB-D video sequences acquired by a vision based Electronic Travel Aid (ETA) for the blind. The achieved door detection performance for the tested sequences is at a level of 63% for sensitivity and 84% for positive predictivity values.