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This paper details a measurement procedure for acquiring growth information on strawberry plants, such as height, width, volume, leaf area, leaf inclination and leaf color using a relatively inexpensive natural interaction device (NID). An NID is a motion-sensing device that is mainly used as a game controller, for example, Microsofts Kinect sensor, that can detect the movements of players by means of a color camera and depth sensor. It captures RGB images of 640 x 480 resolution along with per-pixel depth information. We installed an NID on a circulating-type movable bench system for strawberry cultivation. Since all the plants pass under the NID during the cultivation system, color and depth images of all the plants can be obtained. Using an image-processing method based on grayscale matching, color and depth images of every bench were smoothly tiled. Whole-leaf regions for every bench were then derived. To analyze the color and depth images in the whole-leaf regions efficiently, image-processing software was developed to extract and map the growth information on strawberry plants on the movable bench system. To evaluate the accuracy of our measurement procedure, we compared the actual data on height, width, and leaf area with their estimated values. The results showed each coefficient of determination to exceed 0.8. The maps created revealed significantly local biases of plant growth that varied according to strawberry cultivar.