Adaptive color image processing and recognition for varying backgrounds and illumination conditions

Author

Huang, Wen-Chiang ; Wu, Chwan-Hwa John

Author_Institution

Dept. of Electr. Eng., Auburn Univ., AL, USA

Volume

2

fYear

1997

fDate

9-12 Jun 1997

Firstpage

1381

Abstract

This paper presents a fuzzy based method for recognizing colored objects in a complex background under varying illumination. Fuzzy rules are generated using a Fuzzy Associative Memory (FAM) training method to cope with chromatic distortion. The color model used is the Hue, Saturation, and Value (HSV) color model. The proposed method is applied to stop sign recognition in real-world scenes that may have incorrect video camera focus, color distortions, and varying illumination conditions. Experimental results are reported and analyzed in this paper

Keywords

adaptive signal processing; fuzzy set theory; image colour analysis; inference mechanisms; HSV color model; adaptive color image processing; chromatic distortion; color distortions; color image recognition; color objects; fuzzy associative memory training method; fuzzy based method; incorrect video camera focus; real-world scenes; stop sign recognition; varying backgrounds; varying illumination conditions; Adaptive systems; Cameras; Fuzzy sets; Fuzzy systems; Humans; Image color analysis; Image recognition; Layout; Lighting; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on

Print_ISBN

0-7803-3583-X

Type

conf

DOI

10.1109/ISCAS.1997.622132

Filename

622132