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Aiming at target’s visual information acquisition for robotic management in tomato greenhouse, the method of tracking and measuring the plant’s main-stem was researched, which was supposed to improve the detection efficiency on the object, such as fruit, leaf and flower. According to the tomato’s factory-planted condition in greenhouse, a binocular vision system with two-freedom pan-tilt mechanism was adopted to capture plant’s image and the calibration on the relationship between camera and pan-tilt coordinates data was introduced. The pan-tilt’s servo control method for tracking the plant’s main-stem was proposed, so that the camera could automatically capture the plants bottom-up images. The image matching method for splicing the discrete main-stem in the adjacent view-fields was researched, so as to recover the plant’s image morphology. Based on the 3D coordinate data of a series of tracking reference points, the main-stem’s length, vertical height, and inclination angle could be estimated. Finally, the method for tracking and measuring tomato’s main-stem was tested in greenhouse. As the result showed, in the working area from 600mm to 1500mm high from the ground, the vision system could capture three images of various view-fields, and the main-stem’s average splicing deviation was 3.77°. Compared with manual measurement results, the results of the automatic measurement method on main-stem’s length, vertical height and inclination angle, respectively had the determination coefficients of 0.9933, 0.8426 and 0.9793, and the average deviations of 46.20mm, 18.60mm and 4.33°, respectively. In view of the performance on tracking and measuring target, the method was expected to be a support for researching on tomato’s automatic pruning, harvesting and pollinating.