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Abstract An approach to automate the extraction and measurement of roots in minirhizotron images is presented. Two-dimensional matched filtering is followed by local entropy thresholding to produce binarized images from which roots are detected. After applying a root classifier to discriminate fine roots from unwanted background objects, a root labeling method is implemented to identify each root in the image. Once a root is detected, its length and diameter are measured using Dijkstra’s algorithm for obtaining the central curve and the Kimura-Kikuchi-Yamasaki method for measuring the length of the digitized path. Experimental results from a collection of peach (Prunus persica) root images demonstrate the effectiveness of the approach. Key words root detection, minirhizotron images, matched filtering, thresholding, AdaBoost, Free-man algorith