DocumentCode :
2028436
Title :
A fast traffic sign detection and classification system based on fusion of colour and morphological information
Author :
Khodadadzadeh, Mahdi ; Sarrafzade, Omid ; Ghassemian, Hassan
Author_Institution :
Dept. of Electr. Eng., Tarbiat Modares Univ., Tehran, Iran
fYear :
2010
fDate :
27-28 Oct. 2010
Firstpage :
1
Lastpage :
5
Abstract :
A new method for automatic classification of traffic signs is proposed in this paper. The proposed method is based on the fusion of colour and morphological information. The strategy consists of three steps. First, colour information in HSI colour space is used to segment the input image and finding the region of interests (ROIs) with red pixels. Then, morphological profile is building by employing opening and closing operators on each band of colour image. Next, statistical feature extraction is performed based on both morphological profile and original colour image. Finally, the feature vector is classified by support vector machines based on one-vs.-rest method. The proposed method was tested on domestic database including four classes of red signs. Experimental results show the hit-rate of about 97% in considerably low process time.
Keywords :
driver information systems; feature extraction; image classification; image colour analysis; image fusion; image segmentation; mathematical morphology; object detection; support vector machines; HSI; colour image analysis; colour space; feature vector; image segmentation; information fusion; morphological profile; region of interests; statistical feature extraction; support vector machines; traffic sign classification; traffic sign detection; Feature extraction; Image color analysis; Pixel; Roads; Shape; Support vector machine classification; Data fusion; morphological profile; statistical features; support vector machines (SVMs); traffic sign classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Vision and Image Processing (MVIP), 2010 6th Iranian
Conference_Location :
Isfahan
Print_ISBN :
978-1-4244-9706-5
Type :
conf
DOI :
10.1109/IranianMVIP.2010.5941175
Filename :
5941175
Link To Document :
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