Title :
Automatic LED text recognition method on electronic road sign using local spatial pattern and random forest classifier
Author :
Wahyono ; Filonenko, Alexander ; Kang-Hyun Jo
Author_Institution :
Grad. Sch. of Electr. Eng., Univ. of Ulsan, Ulsan, South Korea
fDate :
June 28 2015-July 1 2015
Abstract :
In the field of intelligent transportation systems (ITS), an electronic road sign (ERS) is an important device for giving a real-time traffic-related information. The ERSs generally display dynamic text information that each character consists of matrix of a light-emitting diodes lamp, named LED text. This paper addresses an LED text detection and recognition method, as an application of ITS for assisting the driver. Our method is divided into several main stages. First, the ERS is localized from the input image using color model on the RGB-color space. Second, LED text contained on the ERS are detected based on supporting points. supporting points representing as a center of LED segment on a binary map of the input image. Third, each character of LED text is recognized using local spatial pattern feature and random forest classifier. Last, the recognized characters are merged into text line. Experimental results verify that the proposed method is robust to detect and recognize the LED text.
Keywords :
LED displays; LED lamps; character recognition; driver information systems; feature extraction; text analysis; ERS; ITS; LED segment; LED text detection; RGB-color space; automatic LED text recognition method; binary map; color model; driver assistance; electronic road sign; intelligent transportation systems; light-emitting diodes lamp; local spatial pattern; local spatial pattern feature; random forest classifier; real-time traffic-related information; Character recognition; Feature extraction; Image color analysis; Light emitting diodes; Roads; Text recognition; Training; LED text recognition; electronic road sign; intelligent transportation systems; local spatial pattern; random forest classifier;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2015 IEEE
Conference_Location :
Seoul
DOI :
10.1109/IVS.2015.7225686