High-throughput phenotyping of crop root system architecture using digital image analysis requires costly special software (WinRHIZO). Novel freeware, ImageJ, has also been developed for the similar pur-pose,butthepresettingofthethresholdtocreaterootbinaryimagesmakesthismethodtime-consuming. This study compares the 16 algorithms available in the ImageJ for processing of rice root images. Among the algorithms, the Triangle algorithm proved to be the best binary method, where the coefficient of cor-relation between ImageJ-estimated and WinRHIZO-estimated root lengths is extremely high (r=0.986). However, using the Triangle algorithm, ImageJ overestimated the rice root length compared with Win-RHIZO. By multiplying the values obtained using ImageJ by 2/3, the estimates closely corresponded to thoseestimatedbyWinRHIZO.ThecorrespondenceofrootlengthsestimatedusingWinRHIZOandImageJ withTrianglealgorithmwasvalidforrootsofvariousmorphologies,andforriceplantsgrowninuplands, rainfed lowlands, and irrigated lowlands. This report proposes the completely automated estimation of rice root length using freeware ImageJ with the appropriate threshold algorithm for image processing.