The current methods of turfgrass evaluations are often based on human-based assessment methods. However, eliminating subjective errors from such evaluations is often impossible. This research compared the accuracy of human-based and digital image processing-based methods for quality assessment of turfgrasses. Four turfgrass plots were evaluated using the two mentioned methods. In the human-based method, 20 evaluators (10 women and 10 men) and in the image-based method, a digital camera with an artificial and controlled light source were used. This experiment for the first time evaluated the two qualitative characteristics of turfgrass texture and weed growth tolerance using a specific image processing-based technique and the common human-based evaluation method. Further, total coverage, color, and living coverage of the turfgrasses were compared with the two methods. The results of the human-based assessment method showed a wider range and higher standard deviations than that in the image processing method, which seems to be due to the differences between the human\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'s evaluators and errors caused by the human mind. The results also emphasized the accuracy and ease of application of the image-processing-based method. This outcome can have applications for developing a mechanized system for turfgrass quality evaluation across the world.

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