Adaptive Exposure Control for Line-Structured Light Sensors Based on Global Grayscale Statistics

Stripe images are crucial for ensuring the measurement quality of line-structured light sensors. To improve the measurement effectiveness of objects with different shapes, materials, and colors, an adaptive exposure method is proposed based on global grayscale statistical analysis of stripe images. The logarithm sum of grayscale statistical results is calculated as the quality evaluation parameter for each stripe image. Theoretical analysis and experiments demonstrate that the proposed quality evaluation value exhibits an approximate linear relationship with a camera's exposure time. Subsequently, an adaptive exposure control method is developed. The influence of control system parameters on measurement results is also analyzed in detail. The experimental results show that our method can adaptively adjust a camera's exposure time according to different surface characteristics. Both the number of effective measurement points and the accuracy are improved.