Title :
LED Traffic Sign Detection Using Rectangular Hough Transform
Author :
GiYeong Bae ; JeongMok Ha ; Jea Young Jeon ; Sung Yong Jo ; Hong Jeong
Author_Institution :
Electr. Eng. Dept., Pohang Univ. Of Sci. & Technol. (POSTECH), Pohang, South Korea
Abstract :
In this paper, a new Advanced Driver Assistant System (ADAS) system for LED traffic sign detection algorithm using rectangle shape based on a windowed hough transform and feature based optimization was presented. We used two character to detect the LED traffic sign. One is LED traffic sign have rectangle shape, another is intensity feature of LED traffic sign. After extracting the candidates of LED traffic signs, our proposed system classify the positive and negative rectangle candidate as a LED traffic sign. Under this flow, we can finally obtained LED traffic sign from real road scene that include LED traffic sign. Our proposed technique was tested in 87 number of real road scene that include LED traffic signs. We can find the 368 number of LED traffic signs of existing 430 number of LED traffic signs. The detection ratio is 85.37%. Algorithm proposed in this paper is very meaningful as a first attempt to detect the LED traffic signs.Detection ratio also reasonable to recognize the traffic sign in the next step of Traffic Sign Recognition (TSR).
Keywords :
Hough transforms; driver information systems; object detection; optimisation; road traffic; ADAS system; LED traffic sign detection algorithm; TSR; advanced driver assistant system system; detection ratio; feature based optimization; rectangular Hough transform; road scene; traffic sign recognition; windowed Hough transform; Feature extraction; Image edge detection; Light emitting diodes; Roads; Shape; Transforms; Vehicles;
Conference_Titel :
Information Science and Applications (ICISA), 2014 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-4443-9
DOI :
10.1109/ICISA.2014.6847422