Preprocessing method of night vision image application in apple harvesting robot

Due to the low working efficiency of apple harvesting robots, there is still a long way to go for commercialization. The machine performance and extended operating time are the two research aspects for improving efficiencies of harvesting robots, this study focused on the extended operating time and proposed a round-the-clock operation mode. Due to the influences of light, temperature, humidity, etc., the working environment at night is relatively complex, and thus restricts the operating efficiency of the apple harvesting robot. Three different artificial light sources (incandescent lamp, fluorescent lamp, and LED lights) were selected for auxiliary light according to certain rules so that the apple night vision images could be captured. In addition, by color analysis, night and natural light images were compared to find out the color characteristics of the night vision images, and intuitive visual and difference image methods were used to analyze the noise characteristics. The results showed that the incandescent lamp is the best artificial auxiliary light for apple harvesting robots working at night, and the type of noise contained in apple night vision images is Gaussian noise mixed with some salt and pepper noise. The preprocessing method can provide a theoretical and technical reference for subsequent image processing.