Document details

Real-time path and obstacle detection for blind persons

Author(s): José, João

Date: 2010

Persistent ID:

Origin: Sapientia - Universidade do Algarve

Project/scholarship: info:eu-repo/grantAgreement/FCT/3599-PPCDT/73633/PT ;

Subject(s): Detecção de passeios; Detecção de obstáculos; Mobilidade; Navegação; Cegos


In this thesis we present algorithms that can be used to improve the mobility of visually impaired persons. First we propose an algorithm to detect the path where the user can walk. This algorithm is based on an adapted version of the Hough transform, in which we apply a method for gathering the most continuous path borders after an edge detector is applied. After an initialization stage we dynamically restrict the area where we look for path borders. This improves accuracy and performance, assuming that the positions of the borders in successive frames are rather stable: images are gathered at a frame rate of at least 5 fps and the user walks at a speed of at most 1 m/s. Other algorithms serve obstacle detection, such that the user can avoid them when walking inside the detected walkable path. To this purpose an obstacle detection window is created, where we look for possible obstacles. The first algorithm applied is based on the zero crossings of vertical and horizontal derivatives of the image. The second algorithm uses the Canny edge detector, separating vertically and horizontally oriented edges to define a region where an obstacle may be. The third algorithm uses Laws’ texture masks in order to verify differences in the ground’s textures. Dynamic thresholds are applied in all algorithms in order to adapt to different pavements. An obstacle is assumed present if the intersection of the regions detected by at least two of the three algorithms is positive in at least three consecutive frames. The algorithms can be used on a modern “netbook” at a frame rate of at least 5 fps, using a normal webcam with VGA resolution (640x480 pixels).

Dissertação de mest., Engenharia Informática, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2010

Document Type Master thesis
Language English
Advisor(s) du Buf, J. M. H.
Contributor(s) José, João
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