Droplet adhesion on target is a common practice in pesticide spray. In order to accurately measure the droplet size and evaluate the distribution, adhesive droplets need to be identified and segmented by image processing. An improved method for judging the droplet adhesion and extracting the features based on droplet shape factor and area threshold of droplets was proposed in this paper. The adhesive droplets were counted by using ultimate erosion and iterative opening operation and segmented by using the watershed algorithm marked with the iterator open operation. The connection areas of the segmented droplets were marked and the shape was rounded. Experimental results showed that the method can effectively extract the characteristics of the adhesion droplets. The accuracy rate of judgment is 100% for weak adhesion and up to 97.2% for strong adhesion. The droplet size obtained by this image process is very close to that measured by laser particle size analyzer. Comparing with Deposit Scan software, this method may improve the size measurement accuracy about 7.67%. Based on the same sample, the comparative analysis showed that the proposed method may obtain the droplet numbers in a much faster speed than the artificial counting and achieved an accuracy of more than 97.06%. The research result also showed that compared with the laser particle size method, the image measurement method was more simple, effective, and suitable for measurement and statistics of the droplet parameters in the field spray experiment.