A High-Frame-Rate Vision System with Automatic Exposure Control

Abstract

Qingyi GU†a) , Abdullah AL NOMAN †b) , Tadayoshi AOYAMA †c) , Takeshi TAKAKI †d) , Nonmembers, and Idaku ISHII †e) , Member SUMMARYIn this paper, we present a high frame rate (HFR) vision system that can automatically control its exposure time by executing brightness histogram-based image processing in real time at a high frame rate. Our aim is to obtain high-quality HFR images for robust image processing of high-speed phenomena even under dynamically changing illumination, such as lamps flickering at 100 Hz, corresponding to an AC power supply at 50 / 60 Hz. Our vision system can simultaneously calculate a 256-bin brightness histogram for an 8-bit gray image of 512×512 pixels at 2000 fps by implementing a brightness histogram calculation circuit module as parallel hardware logic on an FPGA-based high-speed vision platform. Based on the HFR brightness histogram calculation, our method realizes automatic exposure (AE) control of 512×512 images at 2000 fps using our proposed AE algorithm. The proposed AE algorithm can maximize the number of pixels in the effective range of the brightness histogram, thus excluding much darker and brighter pixels, to improve the dynamic range of the captured image without over-and under-exposure. The effectiveness of our HFR system with AE control is evaluated according to experimental results for several scenes with illumination flickering at 100 Hz, which is too fast for the human eye to see. key words: automatic exposure control, high-frame-rate vision system, hardware implementation

Scene Adaptive Exposure Time Control for Imaging and Apparent Motion Sensor

“…In a static scene with A(t − 1) < α (α threshold of magnitude), the camera and subject are static, and the illuminance changes between frames. Exposure time is controlled based on the mean brightness value in the method [10]. Let τ(t) be the exposure time at frame t. The mean brightness value at frame t is p t , and the exposure time τ is adjusted according to the previous frame:…”

A fast automatic exposure adjustment method based on gray and information entropy for space camera

“…At present, numerous studies have been conducted by domestic and foreign scholars for automatic exposure algorithms, such as average luminance values [1][2][3][4][5] , image luminance histograms [6] , information entropy [7] , discrete cosine transform [8] , mathematical iteration [9] , and image fusion [10][11][12] . Gu et al [15] proposed a hardware platform-based automatic dimming algorithm for high-speed cameras. However, the algorithm needs a pair of images with good exposure as a reference for normal operation.…”