Image back-light compensation with fuzzy C-means learning algorithm and fuzzy inferencing

Author

Lin, Daw-Tung ; Chia-Ching Huang

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Chung-Hua Univ., Hsin Chu, Taiwan

Volume

1

fYear

2003

fDate

1-4 July 2003

Firstpage

433

Abstract

In this paper, a two-stage processing technique utilizing the fuzzy c-means learning mechanism and the fuzzy logic rule inference is proposed to compensate the back-light images. The advantages of this approach are: (1) the subject region can be compensated independently, (2) the brightness of subject region can be enhanced without interference of the background, (3) the contrast of subject region can be enhanced adequately, (4) the original background image can be reserved. We have implemented the proposed compensation method and tested on 30 pictures. The performance is better than that of global histogram equalization and global brightness adjustment.

Keywords

fuzzy logic; image colour analysis; image enhancement; image segmentation; back-light image; background image; background interference; color space transformation; fuzzy c-means learning algorithm; fuzzy inferencing; fuzzy logic inference; histogram equalization; image back-light compensation; image compensation; image enhancement; image processing technique; image segmentation; picture processing; subject region brightness; Brightness; Cameras; Clustering algorithms; Color; Equations; Flowcharts; Fuzzy logic; Histograms; Image segmentation; Inference algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on

Print_ISBN

0-7803-7946-2

Type

conf

DOI

10.1109/ISSPA.2003.1224733

Filename

1224733