The clover-grass ratio is an important factor in composing feed ratios for livestock. Cameras in the field allow the user to estimate the clover-grass ratio using image analysis; however, current methods assume the total dry matter is known. This paper presents the preliminary results of an image analysis method for non-destructively estimating the total dry matter of clover-grass. The presented method includes three steps: (1) classification of image illumination using a histogram of the difference in excess green and excess red; (2) segmentation of clover and grass using edge detection and morphology; and (3) estimation of total dry matter using grass coverage derived from the segmentation and climate parameters. The method was developed and evaluated on images captured in a clover-grass plot experiment during the spring growing season. The preliminary results are promising and show a high correlation between the image-based total dry matter estimate and the harvested dry matter ( R 2 = 0.93 ) with an RMSE of 210 kg ha − 1 .