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 GPSVan^TM 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