Research on error analysis and correction methods for binocular ranging in water-rich environments based on backpropagation neural network

The distance measurement based on binocular stereo vision is suitable for online and non-contact target detection because of its advantages including high efficiency, simple system structure and low cost. However, the measurement error will be introduced if the target is on the water (e.g., river and sea), since the optical path changes with the refractive index of the air above the water. The is because the refractive index varies with the temperature, humidity, and atmospheric pressure. Herein, we analyzed the effect of these factors on the measurement error, and proposed model based on backpropagation neural network to predict the measurement error. The error model established in this work provides guidance for the design of accurate binocular ranging systems.