A Video Based Interface to Textual Information for the Visually Impaired
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Progress in Camera-Based Document Image Analysis
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Digit Classification on Signboards for Telephone Number Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
ICDAR 2003 Robust Reading Competitions
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
An automatic sign recognition and translation system
Proceedings of the 2001 workshop on Perceptive user interfaces
Scene Text Extraction in Natural Scene Images using Hierarchical Feature Combining and Verification
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
On the detection of textual information in metro stations
Proceedings of the 7th International Conference on Frontiers of Information Technology
Automatic detection and recognition of Korean text in outdoor signboard images
Pattern Recognition Letters
A head-mounted device for recognizing text in natural scenes
CBDAR'11 Proceedings of the 4th international conference on Camera-Based Document Analysis and Recognition
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Automatic text recognition from natural images receives a growing attention because of potential applications in image retrieval, robotics and intelligent transport system. Camera-based document analysis becomes a real possibility with the increasing resolution and availability of digital cameras. Our research objective is a system that reads the text encountered in natural scenes with the aim to provide assistance to visually impaired persons. In the case of a blind person, finding the text region is the first important problem that must be addressed, because it cannot be assumed that the acquired image contains only characters. In a previous paper [1], we propose four textdetection methods based on connected components. Finding small characters needed significant improvement. This paper describes a new textdetection method geared for small text characters. This method uses Fisher's Discriminant Rate (FDR) to decide whether an image area should be binarized using local or global thresholds. Fusing the new method with a previous morphology-based one yields improved results. Using a controllable webcam and a laptop PC, we developed a prototype that works in real time. At first, our system tries to find in the image areas with small characters. Then it zooms into the found areas to retake higher resolution images necessary for character recognition. Going from this proof-ofconcept to a complete system requires further research effort.