Fast and accurate selection is essential for breeding to cope with rapid climate changes and a steeply increasing population. Consequently, technologies for high-throughput phenotyping (HTP) are emerging. These technologies, unlike conventional phenotyping methods, enable us to evaluate agronomic traits in a fast and massive manner. Thus, the HTP facility was built to acquire and analyze crop images using RGB sensors at the National Institute of Agricultural Sciences, Republic of Korea. By testing various conditions to acquire images, we determined the conditions for phenotyping using the RGB sensor as follows: exposure 30,000 ms, gamma 75, and gain 100 using LED lights in a blue background. Based on this condition, images from 96 individual plants of rice Dongjin cultivar were obtained every week to measure plant height and shoot area, which are directly associated with yield. The results obtained from the image analysis were compared with the manually collected results. The r² value between the projected plant height obtained from image analysis and the plant height obtained from manual measurement was 0.989. Furthermore, the r² value between the projected shoot area obtained from image analysis and the shoot area obtained from manual measurement was 0.981. These results show that image analysis is highly reliable and can be used for crop phenotyping. Therefore, we expect that the new method we developed will be used for breeding in the near future.