Visual substitution system for room labels identification based on text detection and recognition

Abstract

Vision is an essential human sense which is playing the most important role in human perception about surrounding environment. However such information is generally inaccessible for blind people. In order to enable these persons to overcome such incapability, we propose a system for identifying the neighbouring scene. In fact, the environment is labelled as a first step and then we present a personalised and adaptive method for labels detection and recognition. The automatic analysis involves the detection of personalised markers employed to extract the region of interest followed by the perspectives rectification based on homography estimation. We use the stroke width transform (SWT) to extract the text from the detected label and crop it into words and letters. The extracted text is identified using images correlation. Finally, as a substitution for visual modality, a vocal transformation of the recognised text is performed.