Share Email Print
cover

Proceedings Paper

A robust embedded vision system feasible white balance algorithm
Author(s): Yuan Wang; Feihong Yu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm’s performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.

Paper Details

Date Published: 10 January 2018
PDF: 9 pages
Proc. SPIE 10616, 2017 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 1061607 (10 January 2018); doi: 10.1117/12.2287363
Show Author Affiliations
Yuan Wang, Zhejiang Univ. (China)
Feihong Yu, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 10616:
2017 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments
Yongtian Wang; Baohua Jia; Kimio Tatsuno; Liquan Dong, Editor(s)

© SPIE. Terms of Use
Back to Top