DocumentCode :
3279708
Title :
Recognition of colorful objects in variant backgrounds and illumination conditions
Author :
Wen-Chiang Huang ; Wu, Chwan-Hwa John ; Irwan, J.D.
Author_Institution :
Dept. of Electr. Eng., Auburn Univ., AL, USA
fYear :
1996
fDate :
2-6 Dec 1996
Firstpage :
849
Lastpage :
853
Abstract :
This paper presents a fuzzy based method for recognizing color objects in a complex background under varying illumination. Fuzzy rules are generated using a fuzzy associative memory training method to cope with chromatic distortion. The color model used is the hue-saturation-value color model. In this paper, the proposed method is applied to stop sign recognition in real-world scenes that may have incorrect video camera focus and/or other color distortions. The results of this research can help the GPSVanTM system generate maps automatically
Keywords :
adaptive systems; computer vision; fuzzy systems; image colour analysis; inference mechanisms; learning systems; object recognition; road traffic; traffic control; uncertainty handling; GPSVan project; adaptive fuzzy system; chromatic distortion; colorful object recognition; computer vision; fuzzy associative memory; fuzzy reasoning; fuzzy rules; hue-saturation-value color model; illumination; road traffic; stop sign recognition; Adaptive systems; Brightness; Cameras; Color; Databases; Global Positioning System; Histograms; Humans; Layout; Lighting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-3104-4
Type :
conf
DOI :
10.1109/ICIT.1996.601719
Filename :
601719
Link To Document :
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