JRM Vol.30 No.1 pp. 117-127
doi: 10.20965/jrm.2018.p0117


A High-Speed Vision System with Multithread Automatic Exposure Control for High-Dynamic-Range Imaging

Xianwu Jiang*, Qingyi Gu**, Tadayoshi Aoyama***, Takeshi Takaki*, and Idaku Ishii*

*Robotics Laboratory, Graduate School of Engineering, Hiroshima University
1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan

**Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Sciences
No.95 Zhongguancun East Road, Haidian District, Beijing 100190, China

***Department of Micro-Nano Mechanical Science and Engineering, Nagoya University
1 Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan

July 7, 2017
December 5, 2017
February 20, 2018
high-speed vision, AE control, color tracking, HDR imaging

In this study, we develop a real-time high-frame-rate vision system with frame-by-frame automatic exposure (AE) control that can simultaneously synthesize multiple images with different exposure times into a high-dynamic-range (HDR) image for scenarios with dynamic change in illumination. By accelerating the video capture and processing for time-division multithread AE control at the millisecond level, the proposed system can virtually function as multiple AE cameras with different exposure times. This system can capture color HDR images of 512 × 512 pixels in real time at 500 fps by synthesizing four 8-bit color images with different exposure times at consecutive frames, captured at an interval of 2 ms, with pixel-level parallel processing accelerated by a GPU (Graphic Processing Unit) board. Several experimental results for scenarios with a large change in illumination are demonstrated to confirm the performance of the proposed system for real-time HDR imaging.

HDR imaging for dynamic scene

HDR imaging for dynamic scene

Cite this article as:
X. Jiang, Q. Gu, T. Aoyama, T. Takaki, and I. Ishii, “A High-Speed Vision System with Multithread Automatic Exposure Control for High-Dynamic-Range Imaging,” J. Robot. Mechatron., Vol.30 No.1, pp. 117-127, 2018.
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