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Abstract. Proper seed placement during planting is critical to achieve the maximum potential yield of crop. While uniform plant spacing and seeding depth are often used by corn growers to determine the performance of precision planters, these parameters can be influenced by other factors which are not machine related such as germination percentage, diseases and various soil properties. The ideal way to determine planter performance is to measure seed to seed spacing and its ability to maintain a consistent seeding depth during planting. Automating the process would reduce the errors of manual measurement thus providing more reliable information on planter performance for appropriate implementation of planter settings. A computer vision system was developed for automatic measurement of real time seed spacing and seeding depth during planting. The system consisted of a high speed camera, light section sensor and a potentiometer. The generated image mosaics were used to calculate seed spacing wherein it achieved an RMSE of 0.23 and an R² of 0.87. Using the system revealed that the target seeding depth was achieved for 74% of the time during the conduct of the experimental tests. Finally, the system was able to record GPS coordinates of individual images.