ORGB: Offset Correction in RGB Color Space for Illumination-Robust Image Processing

August 03, 2017 · Entered Twilight · 🏛 IEEE International Conference on Acoustics, Speech, and Signal Processing

"No code URL or promise found in abstract"
"Derived repo from GitHub Pages (backfill)"

Evidence collected by the PWNC Scanner

Repo contents: +featmatch, +regseg, README.md, fig_intro.m, h49_1-2.png, shaffer2016mm, tbl_roma.m

Authors Zhenqiang Ying, Ge Li, Sixin Wen, Guozhen Tan arXiv ID 1708.00975 Category cs.CV: Computer Vision Citations 11 Venue IEEE International Conference on Acoustics, Speech, and Signal Processing Repository https://github.com/baidut/ORGB ⭐ 5 Last Checked 7 days ago

Abstract

Single materials have colors which form straight lines in RGB space. However, in severe shadow cases, those lines do not intersect the origin, which is inconsistent with the description of most literature. This paper is concerned with the detection and correction of the offset between the intersection and origin. First, we analyze the reason for forming that offset via an optical imaging model. Second, we present a simple and effective way to detect and remove the offset. The resulting images, named ORGB, have almost the same appearance as the original RGB images while are more illumination-robust for color space conversion. Besides, image processing using ORGB instead of RGB is free from the interference of shadows. Finally, the proposed offset correction method is applied to road detection task, improving the performance both in quantitative and qualitative evaluations.