Top-View-Based Guidance for Blind People Using Directional Ellipse Model

The guidance system proposed in this paper aims to complement the white cane by monitoring road conditions in a medium range for blind pedestrians in real time. The system prototype employs only one webcam fixed at the waist of user. One of the main difficulties of using a single camera in outdoor obstacle detection is the discrimination of obstacles from a complex background. To solve this problem, this paper re-formulates top-view mapping as an inhomogeneous re-sampling process, so that background edges are sub- sampled while obstacle edges are oversampled in the top- view domain. Morphology filters are then used to enhance obstacle edges as edge-blobs, which are further represented using a directional ellipse as a new model for obstacle classification. Based on the identified obstacles, safe walking area is estimated by tracking a polar edge- blob histogram. To transfer the information obtained from image domain to language domain, this paper proposes a verbal message generation scheme based on fuzzy logic. The efficiency of the system is confirmed by testing the system with visually impaired people on outdoor pedestrian paths.