There are many techniques that can be used to estimate the spray quality traits such as the spray coverage, droplet density, droplet count, and droplet diameter. One of the most common techniques is to use water sensitive papers (WSP) as a spray collector on field conditions and analyzing them using several software. However, possible merger of some droplets could occur after they deposit on WSP, and this could affect the accuracy of the results. In this research, image processing technique was used for better estimation of the spray traits, and to overcome the problem of droplet merger. The droplets were classified as non-merged and merged droplets based on their roundness, then the merged droplets were separated based on the average non-merged droplets areas. The results were compared to those which were analyzed using different software. In addition, an analysis was done to samples that were created to simulate the water sensitive paper with pre-known results as a validation. The results showed that separating the droplet based on the developed software increased the coverage, droplet count, and the mean droplet diameter by an average of 1.9, 4.5, and 1.25 times, respectively. This technique showed better estimation of the spray traits using WSP.
