Knowledge of plant roots is important for determining plant-soil relationships, managing soil effectively, studying nutrient and water extraction, and creating a soil quality index. Plant root research is limited by the large amount of time and labor required to wash the roots from the soil and measure the viable roots. A root measurement method based on image analysis was proposed to reduce the time and labor requirement. A thinning algorithm-based image analysis method was used to measure corn root length at the planar faces cut from a core sample. The roots were exposed by careful handling and contrasted from the soil by causing autofluorescence using long-wave ultraviolet light. The contrast-enhanced images were stored on the camcorder video tape and digitized by frame grabber. A binary root image was acquired from the digitized gray scale image by a thresholding operation. The binary root image was thinned until the roots were reduced to their basic structure. Root length was calculated from the number of pixels of the root's basic structure. This root length was divided by the removed soil volume of the profile of the core sample to estimate the root length density (RLD, cm root cm⁻³ soil). This estimated RLD was regressed on RLD, measured from washed roots in the same soil core sample, and a linear relationship (R² = 0.96) was obtained. This study indicated that the image analysis root measurement method can determine the length of corn root systems up to 2.5 times faster than by using the conventional method which incorporates a root washing procedure.