Paper Info
Title
Automatic number recognition for bus route information aid for the visually-impaired
Abstract
In this paper, we propose a number recognition method to quickly and accurately get bus route information for the visually-impaired from natural scenes. We take a boosting approach based on Modified Census Transform (MCT) features, applied with success to number detection. Then, a gradient-based feature extraction algorithm is used to recognize the route number from detected samples. Finally, the recognition result is spoken by the Text-To-Speech (TTS) engine via the speaker embedded in tablet PC so that this information can be used when they take a bus without someone's help. In the experiment, we evaluate the performance of number detection and recognition in our dataset. We achieve high accuracy in both detection and recognition to provide reliable information of the bus routes.
Year
DOI
Venue
2013
10.1109/URAI.2013.6677367
URAI
Keywords
Field
DocType
number recognition,number detection,mct features,modified census transform,text-to-speech engine,learning (artificial intelligence),gradient-based feature extraction algorithm,text detection,image recognition,route number,speech synthesis,feature extraction,notebook computers,the visually-impaired,gradient methods,tts engine,natural scenes,visually-impaired aid,transforms,automatic number recognition,bus route information aid,handicapped aids,tablet pc,adaboost algorithm,learning artificial intelligence
Speech synthesis,Feature extraction algorithm,Pattern recognition,Feature (computer vision),Computer science,Speech recognition,Feature extraction,Census transform,Feature (machine learning),Boosting (machine learning),Artificial intelligence,Text detection
Conference
ISSN
ISBN
Citations 
2325-033X
978-1-4799-1195-0
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Dongjin Lee113.07
Ho-Sub Yoon212710.75
Chankyu Park3186.00
Jaehong Kim438341.59
Cheong Hee Park522322.78