This study analyzes the measurement errors of three dimensional coordinates of binocular stereo vision for tomatoes based on three stereo matching methods, centroid-based matching, area-based matching, and combination matching to improve the localization accuracy of the binocular stereo vision system of tomato harvesting robots. Centroid-based matching was realized through the matching of the feature points of centroids of tomato regions. Area-based matching was realized based on the gray similarity between two neighborhoods of two pixels to be matched in stereo images. Combination matching was realized using the rough disparity acquired through centroid-based matching as the center of the dynamic disparity range which was used in area-based matching. After stereo matching, three dimensional coordinates of tomatoes were acquired using the triangle range finding principle. Test results based on 225 stereo images captured at the distances from 300 to 1000 mm of 3 tomatoes showed that the measurement errors of x coordinates were small, and can meet the need of harvesting robots. However, the measurement biases of y coordinates and depth values were large, and the measurement variation of depth values was also large. Therefore, the measurement biases of y coordinates and depth values, and the measurement variation of depth values should be corrected in the future researches.