Text Detection in Images Based on Unsupervised Classification of Edge-based Features
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Text segmentation based on stroke filter
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Visual door detection integrating appearance and shape cues
Robotics and Autonomous Systems
An Efficient Edge Based Technique for Text Detection in Video Frames
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
Camera-Based signage detection and recognition for blind persons
ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II
RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs
Journal of Visual Communication and Image Representation
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Independent travel is a well known challenge for blind or visually impaired persons. In this paper, we propose a computer vision-based indoor wayfinding system for assisting blind people to independently access unfamiliar buildings. In order to find different rooms (i.e. an office, a lab, or a bathroom) and other building amenities (i.e. an exit or an elevator), we incorporate door detection with text recognition. First we develop a robust and efficient algorithm to detect doors and elevators based on general geometric shape, by combining edges and corners. The algorithm is generic enough to handle large intra-class variations of the object model among different indoor environments, as well as small inter-class differences between different objects such as doors and elevators. Next, to distinguish an office door from a bathroom door, we extract and recognize the text information associated with the detected objects. We first extract text regions from indoor signs with multiple colors. Then text character localization and layout analysis of text strings are applied to filter out background interference. The extracted text is recognized by using off-the-shelf optical character recognition (OCR) software products. The object type, orientation, and location can be displayed as speech for blind travelers.