The spatial distribution of the collectors in dust scrubber is key in determining the effectiveness of the dust removal process. In the present study, a high-speed camera was used to capture images of the distribution of the collectors. Some of the image information was extracted by image processing, such as the gray mean (GM), the angular second moment (ASM), and the entropy (ENT) from the gray-level co-occurrence matrix of the image. Subsequently, the spatial distribution rules of the collectors were studied by analyzing the spatial proportion, dispersion area, and uniformity and intensiveness of the collectors. It is an intuitive approach and a novel analysis method for the operating state of dust scrubber. The results show that the spatial distribution of the collectors could be better reflected by image processing methods. The dispersion area of the collectors expanded with an increase in the airflow velocity. When the initial liquid level (ILL) was higher, the collectors expanded in an approximate circular shape, and when the ILL was lower the collectors expanded in an approximate sector shape. In general, the variation trend in the spatial proportion enhanced with an increase in ILL and airflow velocity, which is consistent with the uniformity of collectors. When the liquid level was 0−20 mm and the airflow velocity was greater than 6.5 m/sec, the spatial proportion and uniformity of the collectors reached the highest degree. However, the growth rate of the spatial proportion and uniformity of the collectors slowed down and even led to negative growth when the ILL was lower and the airflow velocity was higher. The intensiveness of the collectors was great when the ILL was higher, which was free from the apparent influence of the airflow velocity and the ILL. However, when the ILL was lower, the intensiveness of the collectors was poor, intensifying as the airflow velocity and ILL increased. When the liquid level was −5−10 mm and the airflow velocity was greater than 8 m/sec, the intensiveness of the collectors reached the highest degree, indicating that a liquid level greater than 0 mm and a higher airflow velocity improved the spatial distribution of the collectors. Implications: This paper focuses on the spatial distribution of the collectors in dust scrubber. Some of the image information was extracted by image processing, such as the gray mean of the image, the angular second moment, and the entropy from the gray-level co-occurrence matrix of the image. The spatial distribution rules of the collectors were studied by analyzing the spatial proportion, the dispersion area, and the uniformity and intensiveness of the collectors.